Abstract: In the last couple of decades, the research on 3D facial expression recognition has been fostered by the creation of tailored databases containing prototypical expressions of different individuals and by the advances in cost effective acquisition technologies. Though, most of the currently available databases consist of exaggerated facial expressions, due to the imitation principle which they rely on. This makes these databases only partially employable for real world applications such as human-computer interaction for smart products and environments, health, and industry 4.0, as algorithms learn on these ‘inflated’ data which do not respond to ecological validity requirements. In this work, we present two novel 2D + 3D spontaneous facial expression databases of young adults with different geographical origin, in which emotions have been evoked thanks to affective images of the acknowledged IAPS and GAPED databases, and verified with participants’ self-reports. To the best of our knowledge, these are the first three-dimensional facial databases with emotions elicited by validated affective stimuli.

Keywords: 3D facial expression | Affective database | Ecological validity | Facial expression recognition | Human-computer interaction | Spontaneous expressions

Abstract: Protein–protein interaction occurs on surface patches with some degree of complementary geometric and chemical features. Building on this understanding, this study endeavors to characterize the spike protein of the SARS-CoV-2 virus at the morphological and geometrical levels in its Alpha, Delta, and Omicron variants. In particular, the affinity between different SARS-CoV-2 spike proteins and the ACE2 receptor present on the membrane of the human respiratory system cells is investigated. To achieve an adequate degree of geometrical accuracy, the 3D depth maps of the proteins in exam are filtered by developing an ad-hoc convolutional filter with a kernel implemented as a sphere of varying radius, simulating a ball rolling on the surface (similar to the 'rolling ball' filter). This ball ideally models a hypothetical molecule that could interface with the protein and is inspired by the geometric approach to macromolecule–ligand interactions proposed by Kuntz et al. in 1982. The aim is to mitigate the imperfections and to obtain a smoother surface that could be studied from a geometrical perspective for binding purposes. A set of geometric descriptors, borrowed from the 3D face analysis context is then mapped point-by-point onto protein depth maps. Following a feature extraction phase inspired by Histogram of Oriented Gradients and Local Binary Patterns, the final histogram features are used as input for a Support Vector Machine classifier to automatically classify the proteins according to their surface affinity, where a similarity in shape is observed between ACE2 and the spike protein of the SARS-CoV-2 Omicron variant. Finally, Root Mean Square Error analysis is used to quantify the geometrical affinity between the ACE2 receptor and the respective Receptor Binding Domains of the three SARS-CoV-2 variants, culminating in a geometrical explanation for the higher contagiousness of Omicron relative to the other variants under study.

Abstract: Museum institutions represent a narrative tool that can foster a renewed relationship between the community, cultural heritage and the local area. The MEDIA (Advanced Mul-timedia Digital Emotional Museum) project fits into the field of local museum heritage enjoyment and is based on research aimed at investigating visitors’ cognitive and emotional processes through physiological techniques, such as electroencephalography (EEG). Through the case study of the Museum of Valdostan Craftsmanship of Tradition (MAV), this paper explores the potential related to the use of immersive digital technologies, such as virtual reality (VR), to enhance emotional response to heritage and culture and increase user engagement.

Abstract: Developing great products is not simple; users want products that can constantly adjust to their needs. The product development process should consider not only the users’ requirements and wishes but also their perceptions and emotions during and after the human-product interaction. Traditional studies have used self-report methods to study the users’ emotions; however, technological advances are making other methods able to measure respondents’ behavior. Electroencephalography (EEG), a technique for recording and interpreting the brain’s electrical activity, is becoming a valid tool to assess users’ emotional states. This study aims to explore the EEG as a method to interpret emotions. To do this, we created three different VR scenarios characterized by different interior design and automatic chromatic variations as a stimulus; this research aims to analyze if the changes in colors and scenarios reflect on the participants’ emotional responses, specifically on Valence, Arousal, and Engagement. The findings show that EEG results are a valid aid to emotion interpretation; also that color variation might influence users’ emotions and that the emotional responses were more evident when changing between scenarios. We expect this study can provide more information regarding the potential of physiological methods to explore users’ emotions during the product design and development.

Keywords: EEG | Emotional design | Engagement | Product development

Abstract: In the context of human–computer interaction (HCI), understanding user engagement (UE) while interacting with a product or service can provide valuable information for enhancing the design process. UE has been a priority research theme within HCI, as it assesses the user experience by studying the individual’s behavioral response to some stimulus. Many studies looking to quantify the UE are available; however, most use self-report methods that rely only on participants’ answers. This study aims to explore a non-traditional method, specifically electroencephalography, to analyze users’ engagement while interacting with an advergame, an interactive form of advertising in video games. We aim to understand if a more interactive type of advertising will enhance the UE and whether, at the same time, it would influence the user’s purchase intention (UPI). To do this, we computed and compared the UE during the interaction with an advergame and a conventional TV commercial while measuring the participants’ brain activity. After the interaction with both types of advertising, the UPI was also evaluated. The findings demonstrate that a more interactive advertisement increased the participants’ UE and that, in most cases, a UE increment positively influenced the UPI. This study shows an example of the potential of physiological feedback applications to explore the users’ perceptions during and after the human–product interaction. The findings show how physiological methods can be used along with traditional ones for enhancing the UE analysis and provide helpful information about the advantages of engagement measurement in HCI applications.

Keywords: advergames | EEG | purchase intention | user engagement

Abstract: Objectives: The aim of this study was to analyse changes in facial soft tissue thickness (FSTT) after corrective surgeries for dental malocclusion. The correlation between body mass index (BMI) and sex of patients and their FSTT before undergoing surgery was analysed. Materials and methods: Cone beam computed tomography of seventeen patients that underwent Le Fort I osteotomy in combination with bilateral sagittal split osteotomy were collected. Hard and soft tissue landmarks were selected basing on the interventions. FSTT were computed, and measurements from pre- to post-operative were compared. The relationship between FSTT, sex, and BMI was investigated. Results: Considering the comparison between pre- and post-operative measurements, any significant difference emerged (p >.05). The Pearson’s correlation coefficient computed between BMI and the FSTT (pre-operative) showed a correlation in normal-weight patients; the region-specific analysis highlighted a stronger correlation for specific landmarks. Higher median values emerged for women than for men; the subset-based analysis showed that women presented higher values in the malar region, while men presented higher values in the nasal region. Conclusions: The considered surgeries did not affect the FSTT of the patients; differences related to BMI and sex were found. A collection of FSTT mean values was provided for twenty landmarks of pre- and post-operative of female and male subjects. Clinical relevance: This exploratory analysis gave insights on the behaviour of STT after maxillofacial surgeries that can be applied in the development of predictive methodologies for soft tissue displacements and to study modifications in the facial aspect of the patients.

Keywords: Bilateral sagittal split osteotomy (BSSO) | Body mass index (BMI) | Facial landmarks | Le Fort I osteotomy (LFI) | Soft tissue thickness (STT)

Abstract: The research on technologies and methodologies for (accurate, real-time, spontaneous, three-dimensional…) facial expression recognition is ongoing and has been fostered in the past decades by advances in classification algorithms like deep learning, which makes them part of the Artificial Intelligence literature. Still, despite its upcoming application to contexts such as human–computer interaction, product and service design, and marketing, only a few literature studies have investigated the willingness of end users to share their facial data with the purpose of detecting emotions. This study investigates the level of awareness and interest of 373 potential consumers towards this technology in the car insurance sector, particularly in the contract drafting phase, with a focus on differentiating the respondents between generation Y and Z. Results show that younger people, individuals with higher levels of education, and social network users feel more confident about this innovative technology and are more likely to share their expressive facial data.

Keywords: Facial expression recognition | Insurance market | Survey | Technology acceptance | Technology propensity | Young consumers

Abstract: In the last decade, museums and exhibitions have benefited from the advances in Virtual Reality technologies to create complementary virtual elements to the traditional visit. The aim is to make the collections more engaging, interactive, comprehensible and accessible. Also, the studies regarding users’ and visitors’ engagement suggest that the real affective state cannot be fully assessed with self-assessment techniques and that other physiological techniques, such as EEG, should be adopted to gain a more unbiased and mature understanding of their feelings. With the aim of contributing to bridging this knowledge gap, this work proposes to adopt literature EEG-based indicators (valence, arousal, engagement) to analyze the affective state of 95 visitors interacting physically or virtually (in a VR environment) with five handicraft objects belonging to the permanent collection of the Museo dell’Artigianato Valdostano di Tradizione, which is a traditional craftsmanship museum in the Valle d’Aosta region. Extreme Gradient Boosting (XGBoost) was adopted to classify the obtained engagement measures, which were labeled according to questionnaire replies. EEG analysis played a fundamental role in understanding the cognitive and emotional processes underlying immersive experiences, highlighting the potential of VR technologies in enhancing participants’ cognitive engagement. The results indicate that EEG-based indicators have common trends with self-assessment, suggesting that their use as ‘the ground truth of emotion’ is a viable option.

Keywords: craftsmanship | cultural heritage | EEG | user engagement | Virtual Reality | XGBoost

Abstract: Facial appearance is one prominent feature in analyzing several aspects, e.g., aesthetics and expression of emotions, and face analysis is crucial in many fields. Face analysis requires measurements that can be performed by different technologies and typically relies on landmarks identification. Recently, low-cost customer grade 3D cameras have been introduced in the market, enabling an increase of application at affordable cost with nominal adequate performances. Novel cameras require to be thoroughly metrologically characterized to guarantee these performances. Cameras are calibrated following a standard general-purpose procedure. However, the specificity of facial measurements requires a task-based metrological characterization to include typical influence factors. This work outlines a methodology for task-based metrological characterization of low-cost 3D cameras for facial analysis, consisting of: influence factor identification by ANOVA, related uncertainty contribution assessment, uncertainty propagation, landmarking uncertainty estimation. The proposed methodology is then demonstrated on a customer grade state-of-the-art 3D camera available on the market.

Keywords: Depth cameras | Face analysis | Human-machine interaction | Machine vision | Measurement uncertainty | Soft tissue landmarks

Abstract: In the era of ‘metaverse’, virtual environments are gaining popularity among new multimedia contents and are also recognized as a valuable means to deliver emotional content. This is favoured by cost reduction, availability and acceptance by end-users of virtual reality technology. Creating effective virtual environments can be achieved by exploiting several opportunities: creating artificial worlds able to generate different stories, mixing sensory cues, and making the whole interactive. The design space for creating emotional virtual environments is ample, and no clear idea of how to integrate the various components exists. This paper discusses how to combine multiple design elements to elicit five distinct emotions. We developed and tested two scenarios per emotion. We present the methodology, the development of the case studies, and the results of the testing.

Keywords: Affective Virtual Reality | Design Methodology | Emotions | Metaverse | Virtual Reality

Abstract: Building great products or services is not easy; users want products and services that exceed their expectations and evolve with their needs; it is not just about building the right features. Knowing the user engagement (UE) towards a physical, virtual product or service can give valuable information that could be used as feedback for the design, enhancing its chances of success. In the context of user-centered design, UE is the assessment of the user experience characterized by the study of the individual's cognitive, affective, and behavioral response to some stimulus, such as a product, a service, or a website. UE considers not only the users’ requirements and wishes but also their perceptions and reactions during and after an interaction with a product, system, or service. Many studies looking to quantify the UE are available. Still, a framework that provides a generic view of the most commonly used methods and metrics to measure UE does not yet exist in the literature. Aiming to understand the UE better, in this research, we developed a conceptual framework summarizing the available metrics and techniques used across different contexts, including good practices of self-report methods and physiological approaches. We expect this study will allow future researchers, developers, and designers to consider the UE as one of the most prominent product/service success indicators and use this guideline to find the more appropriate method, technique, and metric for its measurement.

Keywords: Consumer engagement | Physiological | UCD | User engagement measurement

Abstract: Despite the great potential of Virtual Reality (VR) to arouse emotions, there are no VR affective databases available as it happens for pictures, videos, and sounds. In this paper, we describe the validation of ten affective interactive Virtual Environments (VEs) designed to be used in Virtual Reality. These environments are related to five emotions. The testing phase included using two different experimental setups to deliver the overall experience. The setup did not include any immersive VR technology, because of the ongoing COVID-19 pandemic, but the VEs were designed to run on stereoscopic visual displays. We collected measures related to the participants’ emotional experience based on six discrete emotional categories plus neutrality and we included an assessment of the sense of presence related to the different experiences. The results showed how the scenarios can be differentiated according to the emotion aroused. Finally, the comparison between the two experimental setups demonstrated high reliability of the experience and strong adaptability of the scenarios to different contexts of use.

Abstract: Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images have been analyzed using a deep learning-based approach, i.e., a convolutional neural network (CNN) specifically trained to perform facial expression recognition (FER). Analyses to assess possible relationships between these results and both ADAS activations and event occurrences, i.e., accidents, have been carried out. A correlation between attention and accidents emerged, whilst facial expressions and ADAS activations resulted to be not correlated, thus no evidence that the designed ADAS are a possible source of distraction has been found. In addition to the experimental results, the proposed approach has proved to be an effective tool to monitor the driver through the usage of non-invasive techniques.

Keywords: ADAS | CNN | DADA | Deep learning | Driver’s attention | RGB-D camera

Abstract: In recent years information and communication technologies (ICT) have played a significant role in all aspects of modern society and have impacted socioeconomic development in sectors such as education, administration, business, medical care and agriculture. The benefits of such technologies in agriculture can be appreciated only if farmers use them. In order to predict and evaluate the adoption of these new technological tools, the technology acceptance model (TAM) can be a valid aid. This paper identifies the most commonly used external variables in e-learning, agriculture and virtual reality applications for further validation in an e-learning tool designed for EU farmers and agricultural entrepreneurs. Starting from a literature review of the technology acceptance model, the analysis based on Quality Function Deployment (QFD) shows that computer self-efficacy, individual innovativeness, computer anxiety, perceived enjoyment, social norm, content and system quality, experience and facilitating conditions are the most common determinants addressing technology acceptance. Furthermore, findings evidenced that the external variables have a different impact on the two main beliefs of the TAM Model, Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). This study is expected to bring theoretical support for academics when determining the variables to be included in TAM extensions.

Keywords: Agriculture | E-learning | QFD | TAM | Technology acceptance | Virtual reality

Abstract: The development of new methods for the correct disposal of waste is unavoidable for any city that aims to become eco-friendly. Waste management is no exception. In the modern era, the treatment and disposal of infectious waste should be seen as an opportunity to generate renewable energy, resource efficiency, and, above all, to improve the population's quality of life. Northern Italy currently produces 66,600 tons/year of infectious waste, mostly treated through incineration plants. This research aims to explore a more ecological and sustainable solution, thereby contributing one more step toward achieving better cities for all. Particularly, this paper presents a conceptual design of the main sterilization chamber for infectious waste. The methodology selected was Design Thinking (DT), since it has a user-centered approach which allows for co-design and the inclusion of the target population. This study demonstrates to the possibility of obtaining feasible results based on the user's needs through the application of DT as a framework for engineering design.

Keywords: Design thinking | Eco-friendly city | Infectious waste | Resource efficiency | Sustainability | Waste management

Abstract: Student engagement allows educational institutions to make better decisions regarding teaching methodologies, methods for evaluating the quality of education, and ways to provide timely feedback. Due to the COVID-19 pandemic, identifying cognitive student engagement in distance learning has been a challenge in higher education institutions. In this study, we implemented a non-self-report method assessing students’ heart rate data to identify the cognitive engagement during active learning activities. Additionally, as a supplementary tool, we applied a previously validated self-report method. This study was performed in distance learning lessons on a group of university students in Bogota, Colombia. After data analysis, we validated five hypotheses and compared the results from both methods. The results confirmed that the heart rate assessment had a statistically significant difference with respect to the baseline during active learning activities, and this variance could be positive or negative. In addition, the results show that if students are previously advised that they will have to develop an a new task after a passive learning activity (such as a video projection), their heart rate will tend to increase and consequently, their cognitive engagement will also increase. We expect this study to provide input for future research assessing student cognitive engagement using physiological parameters as a tool.

Keywords: Active learning | COVID-19 | Distance learning | Heart rate | Higher education | Non-self-report | Self-report | Student engagement

Abstract: Pattern recognition system developers have looked in multiple directions over the years and designed a broad spectrum of methodologies for face identification and verification, both in 2D and 3D. These techniques rely on sound methods and experimentations, and currently give high to excellent recognition rates in terms of performance. Nonetheless, it seems that the most performing face recognition system, especially when familiar faces are involved, is still the human being, able to detect known faces in the wild, in presence of occlusions or extreme light contrast, caricatures, sketches, partial views, blurred images. This is one of the manifold reasons why the human visual system at eye and brain level and face perception techniques are currently being studied by neuroscientists and psychologists, with the aim to uncover the processes underneath the human vision. The purpose of this work is to review the current literature about perception foundations and related biologically-inspired methodologies for face recognition.

Keywords: Biologically-inspired computing | Face expression recognition | Face perception | Face recognition | Human vision | Visual system

Abstract: Supporting education and training initiatives has been identified as an effective way to address Sustainable Development Challenges. In this sense, e-learning stands out as one of the most viable alternatives considering its advantages in terms of resources, time management, and geographical location. Understanding the reasons that move users to adopt these technologies is critical for achieving the desired social objectives. The Technology Acceptance Model (TAM) provides valuable guidelines to identify the variables shaping users’ acceptance of innovations. The present study aims to validate a TAM extension designed for FARMER 4.0, an e-learning application in the agricultural sector. Findings suggest that content quality (CQ) is the primary determinant of farmers’ and agricultural entrepreneurs’ perception of the tool’s usefulness (PU). Furthermore, experience (EXP) and self-efficacy (SE) shape potential users’ perceptions about ease of use (PEOU). This study offers helpful insight into the design and development of e-learning applications in the farming sector and provides empirical evidence of TAM’s validity to assess technology acceptance.

Keywords: Agriculture | E-learning applications | TAM | Technology acceptance

Abstract: Patients with severe facial deformities present serious dysfunctionalities along with an unsatisfactory aesthetic facial appearance. Several methods have been proposed to specifically plan the interventions on the patient’s needs, but none of these seem to achieve a sufficient level of accuracy in predicting the resulting facial appearance. In this context, a deep knowledge of what occurs in the face after bony movements in specific surgeries would give the possibility to develop more reliable systems. This study aims to propose a novel 3D approach for the evaluation of soft tissue zygomatic modifications after zygomatic osteotomy; geometrical descriptors usually involved in face analysis tasks, i.e., face recognition and facial expression recognition, are here applied to soft tissue malar region to detect changes in surface shape. As ground truth for zygomatic changes, a zygomatic openness angular measure is adopted. The results show a high sensibility of geometrical descriptors in detecting shape modification of the facial surface, outperforming the results obtained from the angular evaluation.

Keywords: 3D face analysis | Geometrical descriptors | Malar augmentation | Orthognathic surgery | Soft tissue prediction | Zygomatic osteotomy

Abstract: Background: The aim of this prospective study is to objectively assess 3D soft tissue and bone changes of the malar region by using the malar valgization osteotomy in concomitant association with orthognatic surgery. Materials and methods: From January 2015 to January 2018, 10 patients who underwent single stage bilateral malar valgization osteotomy in conjunction with maxillo-mandibular orthognatic procedures for aesthetic and functional correction were evaluated. Clinical and surgical reports were collected and patient satisfaction was evaluated with a VAS score. For each patient, maxillofacial CT-scans were collected 1 month preoperatively (T0) and 6 months after the operation (T1). DICOM data were imported and elaborated in the software MatLab, which creates a 3D soft tissue model of the face. 3D Bone changes were assessed importing DICOM data into iPlan (BrainLAB 3.0) software and the superimposition process was achieved using autofusion. Descriptive statistical analyses were obtained for soft tissue and bone changes. Results: Considering bone assessment the comparison by superimposition between T0 and T1 showed an increase of the distance between bilateral malar prominence (Pr – Pl) and a slight forward movement (87,65 ± 1,55 to 97,60 ± 5,91); p-value 0.007. All of the patients had improvement of α angle, ranging from 36,30 ± 1,70 to 38,45 ± 0,55, p-value 0,04 (αr) and 36,75 ± 1,58 to 38,45 ± 0,35; p-value 0,04 (αl). The distance S increased from 78,05 ± 2,48 to 84,2 ± 1,20; p-value 0,04 (Sr) and 78,65 ± 2,16 to 82,60 ± 0,90 (Sl); p-value 0,03. Considering the soft tissue, the comparison by superimposition between T0 and T1 showed an antero-lateral movement (p-value 0.008 NVL; p-value 0.001 NVR) of the malar bone projection together with an increase in width measurements (p-value 0,05 VL; p-value 0,01 VR). Angular measurement confirmed the pattern of the bony changes (p-value 0.034 αL; p-value 0,05 αR). Conclusion: The malar valgization osteotomy in conjunction with orthognatic surgery is effective in improving zygomatic projection contributing to a balanced facial correction in midface hypoplasia.3D geometrical based volume and surface analysis demonstrate an increase in transversal and forward direction. The osteotomy can be safely performed in conjunction with orthognatic procedures.

Keywords: Malar augmentation | Orthognatic surgery | Zygomatic osteotomy

Abstract: Computer graphics is-in many cases-about visualizing what you cannot see. However, virtual reality (VR), from its beginnings, aimed at stimulating all human senses: not just the visual channel. Moreover, this set of multisensory stimuli allows users to feel present and able to interact with the virtual environment. In this way, VR aims to deliver experiences that are comparable to real-life ones in their level of detail and stimulation, intensity, and impact. Hence, VR is not only a means to see, but also to feel differently. With the spreading of VR technologies, there is a growing interest in using VR to evoke emotions, including positive and negative ones. This article discusses the current possibilities and the authors' experience collected in the field in trying to elicit emotions through VR. It explores how different design aspects and features can be used, describing their contributions and benefits in the development of affective VR experiences. This work aims at raising awareness of the necessity to consider and explore the full design space that VR technology provides in comparison to traditional media. Additionally, it provides possible tracks of VR affective applications, illustrating how they could impact our emotions and improve our life, and providing guidelines for their development.

Abstract: Artificial Intelligence (AI) algorithms, together with a general increased computational performance, allow nowadays exploring the use of Facial Expression Recognition (FER) as a method of recognizing human emotion through the use of neural networks. The interest in facial emotion and expression recognition in real-life situations is one of the current cutting-edge research challenges. In this context, the creation of an ecologically valid facial expression database is crucial. To this aim, a controlled experiment has been designed, in which thirty-five subjects aged 18–35 were asked to react spontaneously to a set of 48 validated images from two affective databases, IAPS and GAPED. According to the Self-Assessment Manikin, participants were asked to rate images on a 9-points visual scale on valence and arousal. Furthermore, they were asked to select one of the six Ekman’s basic emotions. During the experiment, an RGB-D camera was also used to record spontaneous facial expressions aroused in participants storing both the color and the depth frames to feed a Convolutional Neural Network (CNN) to perform FER. In every case, the prevalent emotion pointed out in the questionnaires matched with the expected emotion. CNN obtained a recognition rate of 75.02%, computed comparing the neural network results with the evaluations given by a human observer. These preliminary results have confirmed that this experimental setting is an effective starting point for building an ecologically valid database.

Keywords: 3D facial database | Affective database | Basic emotions | Ecologically-valid data | Facial expression recognition | Human-robot interaction

Abstract: This article reports on the results of research aimed to translate biometric 3D face recognition concepts and algorithms into the field of protein biophysics in order to precisely and rapidly classify morphological features of protein surfaces. Both human faces and protein surfaces are free-forms and some descriptors used in differential geometry can be used to describe them applying the principles of feature extraction developed for computer vision and pattern recognition. The first part of this study focused on building the protein dataset using a simulation tool and performing feature extraction using novel geometrical descriptors. The second part tested the method on two examples, first involved a classification of tubulin isotypes and the second compared tubulin with the FtsZ protein, which is its bacterial analog. An additional test involved several unrelated proteins. Different classification methodologies have been used: a classic approach with a support vector machine (SVM) classifier and an unsupervised learning with a k-means approach. The best result was obtained with SVM and the radial basis function kernel. The results are significant and competitive with the state-of-the-art protein classification methods. This leads to a new methodological direction in protein structure analysis.

Keywords: 3D face analysis | differential geometry | geometrical descriptors | machine learning | protein classification | support vector machine | tubulin

Abstract: This work aims to identify people psychological stress through the capture of micro modifications and motions within their facial expression. Exogenous and endogenous causes of stress, from environment and/or psychological conditions that could induce stress, have been reproduced in the experimental test involving real subjects, and their face expressions have been recorded by 2D and 3D image capturing tools to create a sample of emotional database. Successively, 2D and 3D analyses have been performed on recorded data according to the respective protocols, by deep learning and machine learning techniques, and a data driven model of the databases has been developed by neural network approach, to classify the psycho-behavioral answers to the different kinds of stress conditions induced on tested people. The ultimate aim of the study is to demonstrate the possibility to analyze data collected on participants from 2D shooting and 3D scans in a consistent way by means of deep learning and machine learning techniques, so that to provide a methodology to identify and classify some of the subtle facial micro-expressions of people involved in stressing activities.

Keywords: Deep learning | Emotion detection | Image recognition | Machine learning | Neural networks

Abstract: Facial Emotion Recognition (FER) is the automatic processing of human emotions by means of facial expression analysis[1]. The most common approach exploits 3D Face Descriptors (3D-FD)[2], which derive from depth maps[3] by using mathematical operators. In recent years, Convolutional Neural Networks (CNNs) have been successfully employed in a wide range of tasks including large-scale image classification systems and to overcome the hurdles in facial expression classification. Based on previous studies, the purpose of the present work is to analyze and compare the abstraction level of 3D face descriptors with abstraction in deep CNNs. Experimental results suggest that 3D face descriptors have an abstraction level comparable with the features extracted in the fourth layer of CNN, the layer of the network having the highest correlations with emotions.

Keywords: Abstraction | CNN | Deep learning | Explainable AI | Facial Emotion Recognition | FER

Abstract: Recently a wide variety of applications has been developed integrating 3D functionalities. Advantages given by the possibility of relying on depth information allows the developers to design new algorithms and to improve the existing ones. In particular, for what concerns face morphology, 3D has led to the possibility to obtain face depth maps highly close to reality and consequently an improvement of the starting point for further analysis such as Face Detection, Face Authentication, Face Identification and Face Expression Recognition. The development of the aforementioned applications would have been impossible without the progress of sensor technologies for obtaining 3D information. Several solutions have been adopted over time. In this paper, emphasis is put on passive stereoscopy, structured light, time-of-flight (ToF) and active stereoscopy, namely the most used technologies for the cameras design and fulfilment according to the literature. The aim of this article is to investigate facial applications and to examine 3D camera technologies to suggest some guidelines for addressing the correct choice of a 3D sensor according to the application that has to be developed.

Keywords: 3D cameras | 3D face analysis | Sensors | Stereoscopy | Structured light | ToF

Abstract: This work proposes an innovative method for evaluating usersâ™ engagement, combining the User Engagement Scale (UES) questionnaire and a facial expression recognition (FER) system, active research topics of increasing interest in the humanâ"computer interaction domain (HCI). The subject of the study is a 3D simulator that reproduces a virtual FabLab in which users can approach and learn 3D modeling software and 3D printing. During the interaction with the virtual environment, a structured-light camera acquires the face of the participant in real-time, to catch its spontaneous reactions and compare them with the answers to the UES closed-ended questions. FER methods allow overcoming some intrinsic limits in the adoption of questioning methods, such as the non-sincerity of the interviewees and the lack of correspondence with facial expressions and body language. A convolutional neural network (CNN) has been trained on the Bosphorus database (DB) to perform expression recognition and the classification of the video frames in three classes of engagement (deactivation, average activation, and activation) according to the model of emotion developed by Russell. The results show that the two methodologies can be integrated to evaluate user engagement, to combine weighted answers and spontaneous reactions and to increase knowledge for the design of the new product or service.

Keywords: 3D simulator | CNN | Deep learning | Facial expression recognition | Human-computer interaction | User engagement scale | User-centered design

Abstract: Common sense usually considers the assessment of female human attractiveness to be subjective. Nevertheless, in the past decades, several studies and experiments showed that an objective component in beauty assessment exists and can be strictly related, even if it does not match, with proportions of features. Proportions can be studied through analysis of the face, which relies on landmarks, i.e., specific points on the facial surface, which are shared by everyone, and measurements between them. In this work, several measures have been gathered from studies in the literature considering datasets of beautiful women to build a set of measures that can be defined as suggestive of female attractiveness. The resulting set consists of 29 measures applied to a public dataset, the Bosphorus database, whose faces have been both analyzed by the developed methodology based on the expanded set of measures and judged by human observers. Results show that the set of chosen measures is significant in terms of attractiveness evaluation, confirming the key role of proportions in beauty assessment; furthermore, the sorting of identified measures has been performed to identify the most significant canons involved in the evaluation.

Keywords: 3D landmarks | Attractiveness | Face analysis | Face proportions | Features extraction

Abstract: Due to its versatility, virtual technology is being widely employed in different domains, from industry to amusement. The possibility to adopt this technology in early product/service design is going to bring positive effects such as the reduction of costs associated with the production of physical prototypes and the generation of a more effective knowledge of users' feedback. This study proposes a preliminary methodology to evaluate users' engagement in interacting with a virtual environment that consists of the integration between a self-report method (the user engagement scale questionnaire) and a method based on facial expression recognition. Results reported in this paper show that the two methodologies generate different types of knowledge which can be used to fit users' needs and expectations. Even if focused on a specific case study, i.e., the evaluation of the engagement in a virtual learning environment, this paper aims to propose a methodology that can be applied to all kinds of virtual products.

Keywords: FER (facial expression recognition) | Product life cycle | Self-reports | Student engagement | Virtual learning environment

Abstract: Three dimensional face analysis is being widely investigated since it appears as a robust solution to overcome the limits of two dimensional technologies. 3D methods allow to relate the recognition process on features not depending on lightning, head poses, make up and occlusions. This paper proposes a new approach to the problem consisting of a novel image representation, where specific facial descriptors replace the RGB traditional channels and a convolutional neural network performs the classification. We chose to use MobileNetV2, a relatively new network, as it has a low amount of parameters to train. The method has been evaluated on the Bosphorus database, and even though it is still a preliminary study, the results obtained with our method are extremely encouraging; the recognition rate achieved is 97.560% and it is comparable to the state of the art. This result, reached despite the fact that the Bosphorus database has a great number of subjects (105) but a low number of scans (4666), shows the effectiveness of this representation combined with convolutional neural networks.

Keywords: 3D face recognition | Curvedness | Deep Convolutional Neural Network | MobileNetV2 | Shape index

Abstract: In pattern recognition, neural networks can be used not only for the classification task, but also for feature selection and other intermediate steps. This paper addresses the 3D face recognition problem in order to select the most meaningful geometric descriptors. At this aim, the classification results are directly integrated in a biclustering process in order to select the best leaves of a neural hierarchical tree. This tree is created by a novel neural network GH-EXIN. This approach results in a new criterion for the feature selection. This technique is applied to a database of face expressions where both traditional and novel geometric descriptors are used. The results state the importance of the curvedness novel descriptors and only of a few Euclidean distances.

Keywords: 3D face recognition | Biclustering | Clustering | Feature selection | GH-EXIN | Neural network

Abstract: This study proposes a novel occlusions detection and restoration strategy. The aim is to success with 3D face recognition even when faces are partially occluded by external objects. The method, which relies on geometrical facial properties, is designed for managing two types of facial occlusions (eye and mouth occlusions due to hands). First occlusions are detected and (if present) classified, by considering their effects on the 3D points cloud. Then, the occluded regions are progressively removed, and finally, the non-occluded symmetrical regions are used to restore the missing information. After the restoration process, face recognition is performed relying on the restored facial information and on the localized landmarks. The landmarking methodology relies on derivatives and on 12 differential geometry descriptors. The discriminating features adopted for facial comparison include shape index histograms, Euclidean and geodetical distances between landmarks, facial curves, and nose volume. Obtained recognition rates, evaluated on the whole Bosphorus database and on our private dataset, ranging from 92.55 to 97.20% depending on the completeness of data.

Keywords: 3D face | Differential geometry | Face analysis | Face recognition | Feature extraction

Abstract: Three-dimensional technologies have had a wide diffusion in several fields of application throughout the last decades; medicine is no exception and the interest in their introduction in clinical applications has grown with the refinement of such technologies. We focus on the application of 3D methodologies in maxillofacial surgery, where they can give concrete support in surgical planning and in the prediction of involuntary facial soft-tissue changes after planned bony repositioning. The purpose of this literature review is to offer a panorama of the existing prediction methods and software with a comparison of their reliability and to propose a series of still pending issues. Various software are available for surgical planning and for the prediction of tissue displacements, but their reliability is still an unknown variable in respect of the accuracy needed by surgeons. Maxilim, Dolphin and other common planning software provide a realistic result, but with some inaccuracies in specific areas of the face; it also is not totally clear how the prediction is obtained by the software and what is the theoretical model they are based on.

Keywords: 3D face analysis | Orthognathic surgery | Prediction methods | Soft tissue prediction | Surgical planning

Abstract: In recent years, facial expression analysis and recognition (FER) have emerged as an active research topic with applications in several different areas, including the human-computer interaction domain. Solutions based on 2D models are not entirely satisfactory for real-world applications, as they present some problems of pose variations and illumination related to the nature of the data. Thanks to technological development, 3D facial data, both still images and video sequences, have become increasingly used to improve the accuracy of FER systems. Despite the advance in 3D algorithms, these solutions still have some drawbacks that make pure three-dimensional techniques convenient only for a set of specific applications; a viable solution to overcome such limitations is adopting a multimodal 2D+3D analysis. In this paper, we analyze the limits and strengths of traditional and deep-learning FER techniques, intending to provide the research community an overview of the results obtained looking to the next future. Furthermore, we describe in detail the most used databases to address the problem of facial expressions and emotions, highlighting the results obtained by the various authors. The different techniques used are compared, and some conclusions are drawn concerning the best recognition rates achieved.

Keywords: 2D/3Dcomparison | 3Dface analysis | Action units | Deep learning-based FER | Facial action coding system | Facial expression recognition

Abstract: Nowadays, facial mimicry studies have acquired a great importance in the clinical domain and 3D motion capture systems are becoming valid tools for analysing facial muscles movements, thanks to the remarkable developments achieved in the 1990s. However, the face analysis domain suffers from a lack of valid motion capture protocol, due to the complexity of the human face. Indeed, a framework for defining the optimal marker set layout does not exist yet and, up to date, researchers still use their traditional facial point sets with manually allocated markers. Therefore, the study proposes an automatic approach to compute a minimum optimized marker layout to be exploited in facial motion capture, able to simplify the marker allocation without decreasing the significance level. Specifically, the algorithm identifies the optimal facial marker layouts selecting the subsets of linear distances among markers that allow to automatically recognizing with the highest performances, through a k-nearest neighbours classification technique, the acted facial movements. The marker layouts are extracted from them. Various validation and testing phases have demonstrated the accuracy, robustness and usefulness of the custom approach.

Keywords: 3D face | Face analysis | Feature extraction | Marker optimization | Motion capture

Abstract: This study proposes a novel quality function deployment (QFD) design methodology based on customers' emotions conveyed by facial expressions. The current advances in pattern recognition related to face recognition techniques have fostered the cross-fertilization and pollination between this context and other fields, such as product design and human-computer interaction. In particular, the current technologies for monitoring human emotions have supported the birth of advanced emotional design techniques, whose main focus is to convey users' emotional feedback into the design of novel products. As quality functional deployment aims at transforming the voice of customers into engineering features of a product, it appears to be an appropriate and promising nest in which to embed users' emotional feedback with new emotional design methodologies, such as facial expression recognition. This way, the present methodology consists in interviewing the user and acquiring his/her face with a depth camera (allowing three-dimensional (3D) data), clustering the face information into different emotions with a support vector machine classificator, and assigning customers' needs weights relying on the detected facial expressions. The proposed method has been applied to a case study in the context of agriculture and validated by a consortium. The approach appears sound and capable of collecting the unconscious feedback of the interviewee.

Keywords: 3D facial expression recognition | Emotional design | Quality function deployment (QFD) | User-centred design

Abstract: As the potentials of technology grow, the embedding of IT advances in different fields and applications increases. A recent example is virtual reality and in particular the virtual product. The possibility of having a product in a virtual form allows creators and designers to efficiently manage the cycle of a product generation and evolution. The key advantage of the “virtual” is to have the product in advance, even in the conceptualization phase, with clear benefits in terms of consumptions of resources and, hence, sustainability. A potential customer could thus interact with a product-to-be and provide feedback about its look and feel, its usability, and, most of all, give an emotional response. In this context, the interaction between the virtual product and the future customer becomes a core point for the new approaches related to user-centred and user experience design, giving birth to a design methodology called “emotional design”. In particular, the study of facial expressions seems to be the more reliable and attractive aspect of it.

Keywords: 3D | Concept design | Emotional design | Facial expression recognition | PLM | Virtual reality

Abstract: Surgical interventions for jaw reconstruction require the design and the production of surgical guides that allow the surgeon to operate quickly and accurately. In some cases, the reconstruction is performed by inserting a prothesis, thus operating exclusively on the jaw, while in other cases the reconstruction is performed by withdrawing and inserting part of the fibula in place of the original jaw bone. This project aims to develop a procedure that allows 3D modeling of the surgical guides necessary for surgical intervention. The idea is to find a surgical guide archetype, a starting shape for the surgeon so that the cutting planes can be oriented without the surgical guide having to be redesigned from scratch for every single patient. The first step of the procedure is the segmentation, performed applying the thresholding operation on the images provided by magnetic resonance MR in order to identify the region of interest (ROI). The second step is the reconstruction of the 3D model, so that a mesh is obtained from 2D images. Subsequently the mesh is post-processed and the cutting plans along which the surgeon will intervene are defined.

Keywords: 3D modeling | 3D reconstruction | Maxillofacial surgery | Surgical guides

Abstract: This paper deals with parenthood perception (maternal and paternal) after the visualization and interaction (touch) with a 3D printed facial fetal model. The model is created using Additive Manufacturing techniques, starting from the image elaboration of routine ultrasound data. In this study, the method used for the elaboration and construction of 3D printable models of fetal faces starting from routine ultrasound images is briefly described. In addition, we present the results of a new survey conducted with future parents at the Altamedica clinic (Rome, Italy) to verify whether there are any benefits derived from the use of 3D printing models with future parents, both regarding the improvement of the parenthood experience, and the improvement of the understanding and collaboration with the physicians in case of fetal malformations, using 3D models coupled with the data of routine ultrasound examinations.

Keywords: 3D ultrasound | Additive manufacturing | Fetal face | Image processing | Parenthood perception | Survey

Abstract: This work proposes a method for recognizing the main 13 Facial Action Units and the 6 basic emotions. The methodologies rely on Differential Geometry to extract relevant discriminant features from the query faces, and on some linear quantities used as measures: Euclidean, geodesic, and angles between 17 automatically extracted soft-tissue landmarks. A thresholding system which evaluates local properties of connected regions, selected through tailored geometrical descriptors, supports the identification of the AUs. Then, a technique based on crisp logic allows the identification of the global expression. The three-dimensional context has been preferred due to its invariance to different lightening/make-up/camouflage conditions.

Keywords: Emotional design | Face expression recognition | Intelligent drive

Abstract: This paper proposes a methodology to assess the discriminative capabilities of geometrical descriptors referring to the public Bosphorus 3D facial database as testing dataset. The investigated descriptors include histogram versions of Shape Index and Curvedness, Euclidean and geodesic distances between facial soft-tissue landmarks. The discriminability of these features is evaluated through the analysis of single block of features and their meanings with different techniques. Multilayer perceptron neural network methodology is adopted to evaluate the relevance of the features, examined in different test combinations. Principle component analysis (PCA) is applied for dimensionality reduction.

Keywords: 3D face recognition | Dimensionality reduction | Geometrical descriptors | Neural network | Principal component analysis

Abstract: This paper proposes a methodology to assess the discriminative capabilities of geometrical descriptors referring to the public Bosphorus 3D facial database as testing dataset. The investigated descriptors include histogram versions of Shape Index and Curvedness, Euclidean and geodesic distances between facial soft-tissue landmarks. The discriminability of these features is evaluated through the analysis of single block of features and their meanings with different techniques. Multilayer perceptron neural network methodology is adopted to evaluate the relevance of the features, examined in different test combinations. Principle Component Analysis (PCA) is applied for dimensionality reduction.

Keywords: 3D face recognition | Dimensionality reduction | Geometrical descriptors | Neural network | Principal component analysis

Abstract: Methodologies for 3D face recognition which work in the presence of occlusions are core for the current needs in the field of identification of suspects, as criminals try to take advantage of the weaknesses among the implemented security systems by camouflaging themselves and occluding their face with eyeglasses, hair, hands, or covering their face with scarves and hats. Recent occlusion detection and restoration strategies for recognition purposes of 3D partially occluded faces with unforeseen objects are here presented in a literature review. The research community has worked on face recognition systems under controlled environments, but uncontrolled conditions have been investigated in a lesser extent. The paper details the experiments and databases used to handle the problem of occlusion and the results obtained by different authors. Lastly, a comparison of various techniques is presented and some conclusions are drawn referring to the best outcomes.

Keywords: 3D face analysis | Face detection | Face recognition | Facial occlusions | Facial restoration

Abstract: This study proposes a novel automatic method for facial landmark localization relying on geometrical properties of 3D facial surface working both on complete faces displaying different emotions and in presence of occlusions. In particular, 12 descriptors coming from Differential Geometry including the coefficients of the fundamental forms, Gaussian, mean, principal curvatures, shape index and curvedness are extracted as facial features and their local geometric properties are exploited to localize 13 soft-tissue landmarks from eye and nose areas. The method is deterministic and is backboned by a thresholding technique designed by studying the behaviour of each geometrical descriptor in correspondence to the locus of each landmark. Occlusions are managed by a detection algorithm based on geometrical properties which allows to proceed with the landmark localization avoiding the covered areas. Experimentations were carried out on 3132 faces of the Bosphorus database and of a 230-sized internal database, including expressive and occluded ones (mouth, eye, and eyeglasses occlusions), obtaining 4.75 mm mean localization error.

Keywords: 3D face | Differential geometry | Face analysis | Feature extraction | Landmark localization

Abstract: Ultrasound scans, Computed Axial Tomography, Magnetic Resonance Imaging are only few examples of medical imaging tools boosting physicians in diagnosing a wide range of pathologies. Anyway, no standard methodology has been defined yet to extensively exploit them and current diagnoses procedures are still carried out mainly relying on physician's experience. Although the human contribution is always fundamental, it is self-evident that an automatic procedure for image analysis would allow a more rapid and effective identification of dysmorphisms. Moving toward this purpose, in this work we address the problem of feature extraction devoted to the detection of specific diseases involving facial dysmorphisms. In particular, a bounded Depth Minimum Steiner Trees (D-MST) clustering algorithm is presented for discriminating groups of individuals relying on the manifestation/absence of the labio-schisis pathology, commonly called cleft lip. The analysis of three-dimensional facial surfaces via Differential Geometry is adopted to extract landmarks. The extracted geometrical information is furthermore elaborated to feed the unsupervised clustering algorithm and produce the classification. The clustering returns the probability of being affected by the pathology, allowing physicians to focus their attention on risky individuals for further analysis.

Keywords: Artificial intelligence | Clustering | D-MST | Decision support | Diagnosis | Facial dysmorphism | Feature extraction | Labio-schisis | Landmarking

Abstract: Open Innovation (OI), a paradigm coined by Chesbrough in 2003, is not only ‘openness towards innovation’, it also represents a firm-view-point-based innovation strategy, which suggests the involvement of external actors in the innovation process. The present paper is part of an on-going discussion on open issues related to OI and the advantages, strengths, challenges and limits of its implementation, dealing with the frequently debated topic of the future of this paradigm. What has emerged from this study is that a clear one-way outline of the OI implementation process does not exist, either in the literature or in practical cases, but common catalyst points, such as a general ‘open’ attitude, the existence of a technology transfer approach, an Intellectual Property protection strategy, and the frequent use of search routines, are identifiable. However, the future of this paradigm is not clear, as the concept may fade away because the process could be fully integrated in the innovation process.

Keywords: creative economy | creative thinking | innovation intermediaries | intellectual property | Open Innovation | SMEs

Abstract: 3D face was recently investigated for various applications, including biometrics and diagnosis. Describing facial surface, i.e. how it bends and which kinds of patches is composed by, is the aim of studies of Face Analysis, whose ultimate goal is to identify which features could be extracted from three-dimensional faces depending on the application. In this study, we propose 105 novel geometrical descriptors for Face Analysis. They are generated by composing primary geometrical descriptors such as mean, Gaussian, principal curvatures, shape index, curvedness, and the coefficients of the fundamental forms, and by applying standard functions such as sine, cosine, and logarithm to them. The new descriptors were mapped on 217 facial depth maps and analysed in terms of descriptiveness of facial shape and exploitability for localizing landmark points. Automatic landmark extraction stands as the final aim of this analysis. Results showed that some newly generated descriptors were sounder than the primary ones, meaning that their local behaviours in correspondence to a landmark position is thoroughly specific and can be registered with high similarity on every face of our dataset.

Keywords: 3D face | Face analysis | Face expression recognition | Face recognition | Geometry | Landmarks

Abstract: This work proposes a methodology to automatically diagnose and formalize prenatal cleft lip with representative key points and identify the type of defect (unilateral, bilateral, right, or left) in three-dimensional ultrasonography (3D US). Differential Geometry has been used as a framework for describing facial shapes and curvatures. Then, descriptors coming from this field are employed for identifying the typical key points of the defect and its dimensions. The descriptive accurateness of these descriptors has allowed us to automatically extract reference points, quantitative distances, labial profiles, and to provide information about facial asymmetry. Seventeen foetal faces, nine of healthy foetuses and eight with different types of cleft lips, have been obtained through a Voluson system and used for testing the algorithm. In case no defect is present, the algorithm detects thirteen standard facial soft-tissue landmarks. This would help ultrasonographists and future mothers in identifying the most salient points of the forthcoming baby. This algorithm has been designed to support practitioners in identifying and classifying cleft lips. The gained results have shown that differential geometry may be a valuable tool for describing faces and for diagnosis.

Keywords: 3D ultrasound | Cleft lip | Dysmorphisms | Landmarking | Syndrome diagnosis

Abstract: This paper deals with additive manufacturing techniques for the creation of 3D fetal face models starting from routine 3D ultrasound data. In particular, two distinct themes are addressed. First, a method for processing and building 3D models based on the use of medical image processing techniques is proposed. Second, the preliminary results of a questionnaire distributed to future parents consider the use of these reconstructions both from an emotional and an affective point of view. In particular, the study focuses on the enhancement of the perception of maternity or paternity and the improvement in the relationship between parents and physicians in case of fetal malformations, in particular facial or cleft lip diseases.

Abstract: As the interest in human face grows, facial landmarks become more and more important for a large variety of fields and applications. Multipurpose medical is evidently leading in this sense, but others such as skull study for crime scenes, sex estimation, and attractiveness quantification, morphological and cephalometric analyses are present. A cluster analysis of the examined papers is performed depending on scope, landmarking method, and facial database features. The purpose is to face these topics by providing the reader with a comprehensive view of what 3D facial landmarks are and what "they have been up to" in 2014 and 2015. The aim is to offer to users the very up-todate scenario, the best outcomes, i.e., the latest frontier of landmarks' talents and skills. The third dimension allowed to select the most prominent contributions, especially in terms of scientific advance innovativeness.

Keywords: 3D face | Cluster analysis | Fiducial point | Landmarks | Soft-tissue landmark, hard-tissue landmark

Abstract: 3D face was recently investigated for various applications, including biometrics and diagnosis. Describing facial surface, i.e. how it bends and which kinds of patches is composed by, is the aim of studies in Face Analysis, whose ultimate goal is to identify which features could be extracted from three-dimensional faces depending on the application. In this study, we propose 54 novel geometrical descriptors for Face Analysis. They are generated by composing primary geometrical descriptors such as mean, Gaussian, principal curvatures, shape index, curvedness, and the coefficients of the fundamental forms. The new descriptors were mapped on 217 facial depth maps and analysed in terms of descriptiveness of facial shape and exploitability for localizing landmark points. Automatic landmark extraction stands as the final aim of this analysis. Results showed that the newly generated descriptors are suitable to 3D face description and to support landmark localization procedures.

Keywords: 3D Face | Face Analysis | Face Recognition | Geometry | Landmarks

Abstract: Ultrasound is by far the most adopted method for safe screening and diagnosis in the prenatal phase, thanks to its non-harmful nature with respect to radiation-based imaging techniques. The main drawback of ultrasound imaging is its sensitivity to scattering noise, which makes automatic tissues segmentation a tricky task, limiting the possible range of applications. An algorithm for automatically extracting the facial surface is presented here. The method provides a comprehensive segmentation process and does not require any human intervention or training procedures, leading from the output of the scanner directly to the 3D mesh describing the face. The proposed segmentation technique is based on a two-step statistical process that relies on both volumetric histogram processing and 2D segmentation. The completely unattended nature of such a procedure makes it possible to rapidly populate a large database of 3D point clouds describing healthy and unhealthy faces, enhancing the diagnosis of rare syndromes through statistical analyses.

Keywords: 3D histogram processing | 3D ultrasound | DICOM | Image segmentation

Abstract: Purpose – Quality function deployment (QFD) is a worldwide-known, design for quality approach, which gathers several design quality methods. Among them, the House of Quality (HoQ) correlates the Voice of Customer and the Voice of Company thanks to L-shaped (2D) Matrix Diagrams (MDs). This paper theorizes, as logically possible, the extension from a bi-dimensional representation (a customer and a provider) to a higher N-dimensional representational freedom without altering the typical QFD’s customer-provider posture. The purpose of this paper is to present QFD 3D: the extension of the Relationship MD in the HoQ toward a third dimension (two customers and a provider or two providers and a customer). Design/methodology/approach – The proposed method is based on an existing well-known quality management tool such as MDs. The authors extend its representational capability by substituting the current L-shaped MDs (2D) with C-shaped ones (3D). The mathematical validity of this extension is described to demonstrate the correctness of the approach. Findings – The paper presents the logical validity and a case study concerning a three-dimensional extension of the Relationship MD in the HoQ, typical of the QFD approach. Research limitations/implications – The results are limited to a three-dimensional extension. Situations where more than three actors are simultaneously involved are theoretically possible, but they are out of the scope of the current research. The difficulty in manipulating 3D representations on traditional supporting tools will be completely reversed on new computer-supported tools. The proposed method is meant to be a useful and efficient instrument for correlating the needs and the services in multi-actors-based scenario, using a QFD design quality approach fueled by IT support tools. Practical implications – This paper can be used as guideline for further researches on N-dimensional extensions of HoQ. The proposed method can be used in a scenario based on the Triple Helix of Innovation. It gives a clear correlation between different needs and services, facilitating the decision-making process and the constitution of a more comprehensive view of the scenario under a quality management approach. Originality/value – Thousands of articles propose different QFD case studies all based on a bi-dimensional correlation between a customer and a provider. This paper proposes a method to extend the pertinence of QFD to scenarios where more than two actors are simultaneously correlated. Considering in particular three actors, the resulting three-dimensional Relationship MD in the HoQ is a totally new design quality tool for correlating customers’ needs and providers’ services. This can result in a significant gain of time and representational ability for quality managers who have to correlate multiple customers with a service provider and conversely a customer to multiple service providers. This approach open the doors for new QFD tools fueled by IT.

Keywords: House of Quality | Matrix diagrams | QFD 3D | Quality function deployment | Quality management | Quality management tool

Abstract: A 3D automatic facial expression recognition procedure is presented in this work. The method is based on point-by-point mapping of seventeen Differential Geometry descriptors onto the probe facial depth map, which is then partitioned into seventy-nine regions. Then, features such as mean, median, mode, volumes, histograms are computed for each region and for each descriptor, to reach a varied large set of parameters representing the query face. Each set of parameters, given by a geometrical descriptor, a region, and a feature, form a trio, whose featuring numerical values are compared with appropriate thresholds, set via experimentation in a previous phase by processing a limited portion of the public facial Bosphorus database. This allows the identification of the emotion-based expression of the query 3D face among the six basic ones (anger, disgust, fear, joy, sadness, surprise). The algorithm was tested on the Bosphorus database and is suitable for applications in security, marketing, medical. The three-dimensional context has been preferred due to its invariance to different lightening/make-up/camouflage conditions.

Keywords: 3D face | Differential geometry | Emotions | Face expression recognition (FER) | Facial expression recognition | Shape index

Abstract: This study proposes a novel approach to automatically localise 11 landmarks from facial RGB images. The novelty of this method relies on the application, i.e., point-by-point mapping, of 11 differential geometry descriptors such as curvatures to the three individual RGB image components. Thus, three-dimensional features are applied to bidimensional facial image representations and used, via thresholding techniques, to extract the landmark positions. The method was tested on the Bosphorus database and showed global average errors lower than five millimetres. The idea behind this approach is to embed this methodology in state-of-the-art 3D landmark detection methods to accomplish a full automatic landmarking by exploiting the advantages of both 2D and 3D data. Some landmarks such as pupils are arduous to be automatically extracted only via three-dimensional techniques. Thus, this method is intended as a bridging-the-gap preliminary technique that takes advantages of 2D imaging only for integrating advanced landmark localisation methodologies.

Keywords: Differential geometry | Face analysis | Facial landmarks | Landmark localisation | RGB images

Abstract: Recent Face Analysis advances have focused the attention on studying and formalizing 3D facial shape. Landmarks, i.e. typical points of the face, are perfectly suited to the purpose, as their position on visage shape allows to build up a map of each human being’s appearance. This turns to be extremely useful for a large variety of fields and related applications. In particular, the forensic context is taken into consideration in this study. This work is intended as a survey of current research advances in forensic science involving 3D facial landmarks. In particular, by selecting recent scientific contributions in this field, a literature review is proposed for in-depth analyzing which landmarks are adopted, and how, in this discipline. The main outcome concerns the identification of a leading research branch, which is landmark-based facial reconstruction from skull. The choice of selecting 3D contributions is driven by the idea that the most innovative Face Analysis research trends work on three-dimensional data, such as depth maps and meshes, with three-dimensional software and tools. The third dimension improves the accurateness and is robust to colour and lightning variations.

Keywords: 3D face | Fiducial point | Forensic | Landmarks | Reconstruction

Abstract: The aim of this work is to automatically diagnose and formalize prenatal cleft lip with representative key points and identify the type of defect (unilateral, bilateral, right, or left) in three-dimensional ultrasonography (3D US). Geometry has been used as a framework for describing facial shapes and curvatures. Then, descriptors coming from this field are employed for identifying the typical key points of the defect and its dimensions. The descriptive accuracy of these descriptors has allowed us to automatically extract reference points, quantitative distances, labial profiles, and to provide information about facial asymmetry. Eighteen foetal faces, ten of healthy foetuses and eight with different types of cleft lips, have been obtained through a Voluson system and used for testing the algorithm. Cleft lip has been diagnosed and correctly characterized in all cases. Transverse and cranio-caudal length of the cleft have been computed and upper lip profile has been automatically extract to have a visual quantification of the overall labial defect. The asymmetry information obtained is consistent with the defect. This algorithm has been designed to support practitioners in identifying and classifying cleft lips. The gained results have shown that geometry might be a proper tool for describing faces and for diagnosis.

Keywords: 3D ultrasound | Cleft lip | Dysmorphisms | Landmarking | Syndrome diagnosis

Abstract: Traditionally, the development of complex mechatronic products, such as products in aerospace or automotive domain, have employed a "document-based" Systems Engineering (SE) approach to perform the systems engineering activities. This approach is characterized by the generation of textual specifications and design documents that are used and exchanged between all project users. Today, innovative interdisciplinary product development requires a rethinking of current methods and IT solutions, employing an efficient Systems Engineering strategy. The goal is to move from a "documentbased" approach to a "model-based" approach that addresses all engineering disciplines. The "Model Based Systems Engineering (MBSE)" methodology is an approach that involves modeling for supporting system requirements definition and management, design, analysis, verification and validation activities. This approach provides a set of data and models that allows design teams to analyze the performances of the different product configurations in an early stage and to ensure product data traceability along the entire product lifecycle maintaining a structured relation between costumer requirements and all the product solution analyzed. At present a shared operative approached aimed at integrating MBSE in a Product Life Cycle Management scenario doesn't exist. For that reason, the paper outlines the key activities to deploy successfully a MBSE methodology, based on the Systems Modeling Language (SysML) within a PLM platform by the use of the Product Functional View.

Keywords: Model-Based Systems Engineering | Product Lifecycle Management | SysML | Systems engineering

Abstract: The application of three-dimensional (3D) facial analysis and landmarking algorithms in the field of maxillofacial surgery and other medical applications, such as diagnosis of diseases by facial anomalies and dysmorphism, has gained a lot of attention. In a previous work, we used a geometric approach to automatically extract some 3D facial key points, called landmarks, working in the differential geometry domain, through the coefficients of fundamental forms, principal curvatures, mean and Gaussian curvatures, derivatives, shape and curvedness indexes, and tangent map. In this article we describe the extension of our previous landmarking algorithm, which is now able to extract eyebrows and mouth landmarks using both old and new meshes. The algorithm has been tested on our face database and on the public Bosphorus 3D database. We chose to work on the mouth and eyebrows as a separate study because of the role that these parts play in facial expressions. In fact, since the mouth is the part of the face that moves the most and affects mainly facial expressions, extracting mouth landmarks from various facial poses means that the newly developed algorithm is pose-independent.

Keywords: 3D face | 3D scanner | Differential geometry | Face morphology | Medical diagnosis | Soft-tissue landmarks

Abstract: Product lifecycle management (PLM) is increasingly important for organizations acting in dynamic and competitive markets since PLM can improve decision-making and reduce costs by taking advantage of the efficiencies and effectiveness coming from improved market intelligence and collaboration of partners. In the last years, academics as well as practitioners and consultants have developed a wide range of maturity models for the purpose of measuring and describing certain aspects of PLM "maturity". The PLM maturity models permit to assess the relative position of companies on their road to complete PLM implementation. However, it is a tough job for the company to select the most appropriate PLM maturity model, as each maturity model has different attributes. Since, to our knowledge, no benchmarking for PLM maturity models exists to date, the rising number of maturity models implicates problems with respect to retrievability and reusability. With the aim to enhance the time consuming and exhausting search and selection process of appropriate assessment models, a benchmarking framework for PLM maturity models is presented in this paper. © 2013 Springer-Verlag London.

Keywords: Capability maturity model (CMM) | Maturity models | Product lifecycle management (PLM)

Abstract: The face is perhaps the most important human anatomical part, and its study is very important in many fields, such as the medical one and the identification one. Technical literature presents many works on this topic involving bi-dimensional solutions. Even if these solutions are able to provide interesting results, they are strongly subjected to images distortion. Thanks to the significant improvements obtained in the 3D scanner domain (photogrammetry for instance), today it is possible to replace the 2D images with more precise and complete 3D models (triangulated points clouds). Working on three-dimensional data, in fact, it is possible to obtain a more complete set of information about the face morphology. At present, even if it is possible to find interesting papers on this field, there is the lack of a complete protocol for converting the big amount of data coming from the three-dimensional point clouds in a reliable set of facial data, which could be employed for recognition and medical tasks. Starting from some anatomical human face concepts, it has been possible to understand that some soft-tissue landmarks could be the right data set for supporting many processes working on three-dimensional models. So, working in the Differential Geometry domain, through the Coefficients of the Fundamental Forms, the Principal Curvatures, Mean and Gaussian Curvatures and also with the derivatives and the Shape and Curvedness Indexes, the study has proposed a structured methodology for soft-tissue landmark formalization in order to provide a methodology for their automatic identification. The proposed methodology and its sensitivity have been tested with the involvement of a series of subjects acquired in different scenarios. © 2012 Springer Science+Business Media, LLC.

Keywords: 3D models | 3D scanners | Face morphology | Soft tissue landmarks

Abstract: In the last decade, three-dimensional landmarking has gained attention for different applications, such as face recognition for both identification of suspects and authentication, facial expression recognition, corrective and aesthetic surgery, syndrome study and diagnosis. This work focuses on the last one by proposing a geometrically-based landmark extraction algorithm aimed at diagnosing syndromes on babies before their birth. Pivotal role in this activity is the support provided by physicians and 3D ultrasound tools for working on real faces. In particular, the landmarking algorithm here proposed only relies on descriptors coming from Differential Geometry (Gaussian, mean, and principal curvatures, derivatives, coefficients of first and second fundamental forms, Shape and Curvedness indexes) and is tested on nine facial point clouds referred to nine babies taken by a three-dimensional ultrasound tool at different weeks' gestation. The results obtained, validated with the support of four practitioners, show that the localization is quite accurate. All errors lie in the range between 0 and 3.5 mm and the mean distance for each shell is in the range between 0.6 and 1.6 mm. The landmarks showing the highest errors are the ones belonging to the mouth region. Instead, the most precise landmark is the pronasal, on the nose tip, with a mean distance of 0.55 mm. Relying on current literature, this study is something missing in the state-of-the-art of the field, as present facial studies on 3D ultrasound do not work on automatic landmarking yet.

Keywords: 3D echography | 3D face | 3D ultrasound | Dysmorphisms | Landmarking | Syndrome diagnosis

Abstract: In the last decades, several three-dimensional face recognition algorithms have been thought, designed, and assessed. What they have in common can be hardly said, as they differ in theoretical background, tools, and method. Here we propose a new 3D face recognition algorithm, entirely developed in Matlab ® ,whose framework totally comes from differential geometry. First, 17 soft-tissue landmarks are automatically extracted relying on geometrical properties of facial shape. We made use of derivatives, coefficients of the fundamental forms, principal, mean, and Gaussian curvatures, and shape and curvedness indexes. Then, a set of geodesic and Euclidean distances, together with nose volume and ratios between geodesic and Euclidean distances, has been computed and summed in a final score, used to compare faces. The highest contribution of this work, we believe, is that its theoretical substratum is differential geometry with its various descriptors, which is something totally new in the field.

Keywords: 3D face | Face recognition | Geodesic distance | Geometry | Landmark | Shape index

Abstract: Face study and description through landmarks is a key activity in many fields, in particular the medical one for both corrective and esthetic surgery purposes. In a previous work, we used a geometric approach to automatically extract landmarks working in the Differential Geometry domain, through the coefficients of the Fundamental Forms, the Principal Curvatures, Mean and Gaussian Curvatures, derivatives, and Shape and Curvedness Indexes. In this paper we describe the improvements made to our previously developed algorithm by using a new parameterization of the mesh, new geometrical descriptors, and new conditions. © 2013 Elsevier B.V. All rights reserved.

Keywords: 3D face | 3D scanner | Differential Geometry | Face morphology | Soft-tissue landmark extraction

Abstract: The literature on Open Innovation is booming. In recent years, more and more contributions have been published in several scientific reviews. This increasing trend calls for an approach that could lead to a classification of the specificities of these contribution contents. This is what this paper aims to do. More specifically, our goal is to provide not a simple catalogue of the hundreds of articles published in this field, but rather it tries by cluster analysis a classification of the most important key features of the typical articles published in the field of Open Innovation, with a specific focus on implemented methods in SMEs. Notwithstanding the limitations of our attempt, the cluster analysis results provide a reference paradigm to compare existing as well as future contributions and add new insights. This paper highlights how a path dependence approach in the literature has influenced the companies Open Innovation implementation, but some recent attempts at overcoming this process are arising. This recent trend focuses on SMEs as the real key challenge. Copyright © 2013 Inderscience Enterprises Ltd.

Keywords: Methods for SMEs | Open innovation | Path dependence

Abstract: Recently, 3D landmark extraction has been widely researched and experimented in medical field, for both corrective and aesthetic purposes. Automation of these procedures on three-dimensional face renderings is something desirable for the specialists who work in this field. In this work we propose a new method for accurate landmark localization on facial scans. The method relies on geometrical descriptors, such as curvatures and Shape Index, for computing candidate and initial points, and on a statistical model based on Procrustes Analysis and Principal Component Analysis, which is fitted to candidate points, for extracting the final landmarks. The elaborated method is independent on face pose. © 2012 Elsevier Ireland Ltd.

Keywords: 3D face | Differential Geometry | Landmark extraction | PCA | Procrustes Analysis

Abstract: Distance measures and geometrical features are widely used to describe faces. Generally, they are extracted punctually from landmarks, namely anthropometric reference points. The aims are various, such as face recognition, facial expression recognition, face detection, study of changes in facial morphology due to growth, or dysmorphologies. Most of the time, landmarks were extracted with the help of an algorithm or manually located on the faces. Then, measures are computed or geometrical features are extracted to perform the scope of the study. This paper is intended as a survey collecting and explaining all these features, in order to provide a structured user database of the potential parameters and their characteristics. Firstly, facial soft-tissue landmarks are defined and contextualized; then the various measures are introduced and some results are given; lastly, the most important measures are compared to identify the best one for face recognition applications. © 2012 Elsevier B.V. All rights reserved.

Keywords: 3D models | 3D scanners | Face morphology | Soft tissue landmarks

Abstract: The face is one of the most important parts of the human anatomy, and its study is very important, especially for developing automatic public security recognition strategies. In order to support this field, it is necessary to find a formal way of converting what the human eyes normally do in recognizing one person from another by extracting implicitly some morphological features. Since human recognition happens through an automatic "authentication" of facial shape and features, this study should be undertaken in the geometrical domain. The technical literature shows many parameters that could be adopted for finding a solution to this problem, but at present there is no evidence of a reliable solution. For this reason, this work, analysing strengths and constraints of what is available in the geometrical domain, provides the first guideline for supporting the development of an automatic face recognition approach. Starting from differential geometry, such as the coefficients of the fundamental forms, the principal curvatures, mean and Gaussian curvatures, the derivatives and the shape and curvedness indices introduced by Koenderink and VanDoorn, this paper, working on a consistent set of case studies, analyses the geometrical descriptors' performances in the three-dimensional facial study by the use of a set of indicators (similarity between different faces, sensitivity to noise, etc.). This is a preliminary study for analysing the behaviours of these descriptors on faces. It may be used as a guideline or a theoretical framework for researchers studying face shape or for face recognition applications. © 2012 Elsevier B.V. All rights reserved.

Keywords: 3D scanners | Differential geometry | Face morphometry | Geometrical descriptors | Geometrical human modelling