Com o avanço da tecnologia, as estratégias tradicionais para identificação de pessoas se tornaram mais suscetíveis a falhas. De forma a superar essas dificuldades algumas abordagens vêm sendo propostas na literatura. Dentre estas abordagens destaca-se a Biometria. O campo da Biometria abarca uma grande variedade de tecnologias usadas para identificar ou verificar a identidade de uma pessoa por meio da mensuração e análise de aspectos físicos e/ou comportamentais do ser humano. Em função disso, a biometria tem um amplo campo de aplicações em sistemas que exigem uma identificação segura de seus usuários. Os sistemas biométricos mais populares são baseados em reconhecimento facial ou em impressões digitais. Entretanto, existem sistemas biométricos que utilizam a íris, varredura de retina, voz, geometria da mão e termogramas faciais. Atualmente, tem havido progresso significativo em reconhecimento automático de face em condições controladas. Em aplicações do mundo real, o reconhecimento facial sofre de uma série de problemas nos cenários não controlados. Esses problemas são devidos, principalmente, a diferentes variações faciais que podem mudar muito a aparência da face, incluindo variações de expressão, de iluminação, alterações da pose, assim como oclusões parciais. Em comparação com o grande número de trabalhos na literatura em relação aos problemas de variação de expressão/iluminação/pose, o problema de oclusão é relativamente negligenciado pela comunidade científica. Embora tenha sido dada pouca atenção ao problema de oclusão na literatura de reconhecimento facial, a importância deste problema deve ser enfatizada, pois a presença de oclusão é muito comum em cenários não controlados e pode estar associada a várias questões de segurança. Por outro lado, a Multibiométria é uma abordagem relativamente nova para representação de conhecimento biométrico que visa consolida múltiplas fontes de informação visando melhorar a performance do sistema biométrico. Multibiométria é baseada no conceito de que informações obtidas a partir de diferentes modalidades ou da mesma modalidade capturada de diversas formas se complementam. Consequentemente, uma combinação adequada dessas informações pode ser mais útil que o uso de informações obtidas a partir de qualquer uma das modalidades individualmente. A fim de melhorar a performance dos sistemas biométricos faciais na presença de oclusão parciais será investigado o emprego de diferentes técnicas de reconstrução de oclusões parciais de forma a gerar diferentes imagens de face, as quais serão combinadas no nível de extração de característica e utilizadas como entrada para um classificador neural. Os resultados demonstram que a abordagem proposta é capaz de melhorar a performance dos sistemas biométricos baseados em face parcialmente ocluídas / With the advancement of technology, traditional strategies for identifying people have become more susceptible to failures. In order to overcome these difficulties, some approaches have been proposed in the literature. Among these approaches, Biometrics stands out. The field of biometrics covers a wide range of technologies used to identify or verify a person\'s identity by measuring and analyzing physical and / or behavioral aspects of the human being. As a result, a biometry has a wide field of applications in systems that require a secure identification of its users. The most popular biometric systems are based on facial recognition or fingerprints. However, there are biometric systems that use the iris, retinal scan, voice, hand geometry, and facial thermograms. Currently, there has been significant progress in automatic face recognition under controlled conditions. In real world applications, facial recognition suffers from a number of problems in uncontrolled scenarios. These problems are mainly due to different facial variations that can greatly change the appearance of the face, including variations in expression, illumination, posture, as well as partial occlusions. Compared with the large number of papers in the literature regarding problems of expression / illumination / pose variation, the occlusion problem is relatively neglected by the research community. Although attention has been paid to the occlusion problem in the facial recognition literature, the importance of this problem should be emphasized, since the presence of occlusion is very common in uncontrolled scenarios and may be associated with several safety issues. On the other hand, multibiometry is a relatively new approach to biometric knowledge representation that aims to consolidate multiple sources of information to improve the performance of the biometric system. Multibiometry is based on the concept that information obtained from different modalities or from the same modalities captured in different ways complement each other. Accordingly, a suitable combination of such information may be more useful than the use of information obtained from any of the individuals modalities. In order to improve the performance of facial biometric systems in the presence of partial occlusion, the use of different partial occlusion reconstruction techniques was investigated in order to generate different face images, which were combined at the feature extraction level and used as input for a neural classifier. The results demonstrate that the proposed approach is capable of improving the performance of biometric systems based on partially occluded faces

Com o avanço da tecnologia, as estratégias tradicionais para identificação de pessoas se tornaram mais suscetíveis a falhas. De forma a superar essas dificuldades algumas abordagens vêm sendo propostas na literatura. Dentre estas abordagens destaca-se a Biometria. O campo da Biometria abarca uma grande variedade de tecnologias usadas para identificar ou verificar a identidade de uma pessoa por meio da mensuração e análise de aspectos físicos e/ou comportamentais do ser humano. Em função disso, a biometria tem um amplo campo de aplicações em sistemas que exigem uma identificação segura de seus usuários. Os sistemas biométricos mais populares são baseados em reconhecimento facial ou em impressões digitais. Entretanto, existem sistemas biométricos que utilizam a íris, varredura de retina, voz, geometria da mão e termogramas faciais. Atualmente, tem havido progresso significativo em reconhecimento automático de face em condições controladas. Em aplicações do mundo real, o reconhecimento facial sofre de uma série de problemas nos cenários não controlados. Esses problemas são devidos, principalmente, a diferentes variações faciais que podem mudar muito a aparência da face, incluindo variações de expressão, de iluminação, alterações da pose, assim como oclusões parciais. Em comparação com o grande número de trabalhos na literatura em relação aos problemas de variação de expressão/iluminação/pose, o problema de oclusão é relativamente negligenciado pela comunidade científica. Embora tenha sido dada pouca atenção ao problema de oclusão na literatura de reconhecimento facial, a importância deste problema deve ser enfatizada, pois a presença de oclusão é muito comum em cenários não controlados e pode estar associada a várias questões de segurança. Por outro lado, a Multibiométria é uma abordagem relativamente nova para representação de conhecimento biométrico que visa consolida múltiplas fontes de informação visando melhorar a performance do sistema biométrico. Multibiométria é baseada no conceito de que informações obtidas a partir de diferentes modalidades ou da mesma modalidade capturada de diversas formas se complementam. Consequentemente, uma combinação adequada dessas informações pode ser mais útil que o uso de informações obtidas a partir de qualquer uma das modalidades individualmente. A fim de melhorar a performance dos sistemas biométricos faciais na presença de oclusão parciais será investigado o emprego de diferentes técnicas de reconstrução de oclusões parciais de forma a gerar diferentes imagens de face, as quais serão combinadas no nível de extração de característica e utilizadas como entrada para um classificador neural. Os resultados demonstram que a abordagem proposta é capaz de melhorar a performance dos sistemas biométricos baseados em face parcialmente ocluídas / With the advancement of technology, traditional strategies for identifying people have become more susceptible to failures. In order to overcome these difficulties, some approaches have been proposed in the literature. Among these approaches, Biometrics stands out. The field of biometrics covers a wide range of technologies used to identify or verify a person\'s identity by measuring and analyzing physical and / or behavioral aspects of the human being. As a result, a biometry has a wide field of applications in systems that require a secure identification of its users. The most popular biometric systems are based on facial recognition or fingerprints. However, there are biometric systems that use the iris, retinal scan, voice, hand geometry, and facial thermograms. Currently, there has been significant progress in automatic face recognition under controlled conditions. In real world applications, facial recognition suffers from a number of problems in uncontrolled scenarios. These problems are mainly due to different facial variations that can greatly change the appearance of the face, including variations in expression, illumination, posture, as well as partial occlusions. Compared with the large number of papers in the literature regarding problems of expression / illumination / pose variation, the occlusion problem is relatively neglected by the research community. Although attention has been paid to the occlusion problem in the facial recognition literature, the importance of this problem should be emphasized, since the presence of occlusion is very common in uncontrolled scenarios and may be associated with several safety issues. On the other hand, multibiometry is a relatively new approach to biometric knowledge representation that aims to consolidate multiple sources of information to improve the performance of the biometric system. Multibiometry is based on the concept that information obtained from different modalities or from the same modalities captured in different ways complement each other. Accordingly, a suitable combination of such information may be more useful than the use of information obtained from any of the individuals modalities. In order to improve the performance of facial biometric systems in the presence of partial occlusion, the use of different partial occlusion reconstruction techniques was investigated in order to generate different face images, which were combined at the feature extraction level and used as input for a neural classifier. The results demonstrate that the proposed approach is capable of improving the performance of biometric systems based on partially occluded faces

La zeitgesit contemporaine sur la reconnaissance des visages suggère que le processus de reconnaissance reposerait essentiellement sur le traitement des distances entre les attributs internes du visage. Il est toutefois surprenant de noter que cette hypothèse n’a jamais été évaluée directement dans la littérature. Pour ce faire, 515 photographies de visages ont été annotées afin d’évaluer l’information véhiculée par de telles distances. Les résultats obtenus suggèrent que les études précédentes ayant utilisé des modifications de ces distances ont présenté 4 fois plus d’informations que les distances inter-attributs du monde réel. De plus, il semblerait que les observateurs humains utilisent difficilement les distances inter-attributs issues de visages réels pour reconnaître leurs semblables à plusieurs distances de visionnement (pourcentage correct maximal de 65%). Qui plus est, la performance des observateurs est presque parfaitement restaurée lorsque l’information des distances inter-attributs n’est pas utilisable mais que les observateurs peuvent utiliser les autres sources d’information de visages réels. Nous concluons que des indices faciaux autre que les distances inter-attributs tel que la forme des attributs et les propriétés de la peau véhiculent l’information utilisée par le système visuel pour opérer la reconnaissance des visages. / According to an influential view, based on studies of development and of the face inversion effect, human face recognition relies mainly on the treatment of the distances among internal facial features. However, there is surprisingly little evidence supporting this claim. Here, we first use a sample of 515 face photographs to estimate the face recognition information available in interattribute distances. We demonstrate that previous studies of interattribute distances generated faces that exaggerated 4 times this information compared to real-world faces. When interattribute distances are sampled from a real-world distribution, we show that human observers recognize faces poorly across a broad range of viewing distances (with a maximum accuracy of 65%). In contrast, recognition performance is restored when observers only use facial cues of real-world faces other than interattribute distances. We conclude that facial cues other than interattribute distances such as attribute shapes and skin properties are the dominant information of face recognition mechanisms.

Contexte : la présence d’un biais cognitif négatif chez les individus qui souffrent de dépression majeure (DM) et ceux qui y sont à haut risque (e.g. enfants de mères qui souffrent de DM) est maintenant établie. Aucune étude portant sur la vulnérabilité cognitive (VC) des membres de la fratrie n’est rapportée. Objectifs : la présente étude a pour but de vérifier si la fratrie des adolescents qui souffrent de DM présentent une VC qui les prédisposent à la DM. Méthode : cette étude porte sur 49 adolescents (18 participants traités pour une DM, 16 membres de la fratrie et 15 participants témoin), âgés entre 12 et 20 ans. La VC de chaque participant est quantifiée via un questionnaire qui mesure la réactivité cognitive (RC), soit le LEIDS-R, et une tâche de reconnaissance des expressions faciale (REF). La cognition sociale des participants est mesurée par le MASC, un outil qui évalue la cognition sociale par médium vidéo et que notre équipe a traduit de l’allemand au français. Résultats : les résultats préliminaires de la présente étude indiquent qu’une différence de réactivité cognitive est présente entre les adolescents traités pour une DM et les participants du groupe témoin (p < 0,001). L’analyse préliminaire tend à indiquer qu’une différence est présente entre la fratrie et le groupe contrôle. Conclusion : plusieurs de nos résultats tendent en faveur de la présence d’une VC prédisposant à la DM chez la fratrie des adolescents souffrant de DM. Ces résultats préliminaires doivent être confirmés par des études longitudinales. / Background: a negative cognitive bias is present among individuals who suffers from major depression. This bias is also reported among individuals at high risk of major depression (e.g. child of depressed mother). No study to date aimed to evaluate cognitive vulnerability of siblings of depressed individuals. Objectives: the present study aim to verify if siblings of depressed adolescents present a cognitive vulnerability that would predispose them to develop a major depression. Method: This study evaluates 49 adolescents (18 participants treated for depression, 16 siblings and 15 controls), aged between 12 and 20 years old. The cognitive vulnerability of every participant has been assessed using an auto-report questionnaire of symptoms (LEIDS-R) that evaluates cognitive reactivity and a task of facial recognition. Social cognition of participants is measured using the Movie for Assessment of Social Cognition (MASC) that we translated from german to french. Results: the preliminary analyses of this study concludes that a significant difference of cognitive reactivity is present between adolescents treated for depression and controls (p < 0.001). Conclusion: some of our results tend to confirm the presence of a cognitive vulnerability to depression among siblings of depressed adolescents. Those results are still preliminary and need to be confirmed by longitudinal studies. / Réalisé sous la co-direction de Linda Booij, Catherine Herba et Patricia Garel

Historiquement et socialement, le visage est chez l'humain une modalité de prédilection pour déterminer l'identité et l'état émotionnel d'une personne. Il est naturellement exploité en vision par ordinateur pour les problèmes de reconnaissance de personnes et d'émotions. Les algorithmes d'analyse faciale automatique doivent relever de nombreux défis : ils doivent être robustes aux conditions d'acquisition ainsi qu'aux expressions du visage, à l'identité, au vieillissement ou aux occultations selon le scénario. La modalité 3D a ainsi été récemment investiguée. Elle a l'avantage de permettre aux algorithmes d'être, en principe, robustes aux conditions d'éclairage ainsi qu'à la pose. Cette thèse est consacrée à l'analyse de visages en 3D, et plus précisément la reconnaissance faciale ainsi que la reconnaissance d'expressions faciales en 3D sans texture. Nous avons dans un premier temps axé notre travail sur l'apport que pouvait constituer une approche régions aux problèmes d'analyse faciale en 3D. L'idée générale est que le visage, pour réaliser les expressions faciales, est déformé localement par l'activation de muscles ou de groupes musculaires. Il est alors concevable de décomposer le visage en régions mimiques et statiques, et d'en tirer ainsi profit en analyse faciale. Nous avons proposé une paramétrisation spécifique, basée sur les distances géodésiques, pour rendre la localisation des régions mimiques et statiques le plus robustes possible aux expressions. Nous avons également proposé une approche régions pour la reconnaissance d'expressions du visage, qui permet de compenser les erreurs liées à la localisation automatique de points d'intérêt. Les deux approches proposées dans ce chapitre ont été évaluées sur des bases standards de l'état de l'art. Nous avons également souhaité aborder le problème de l'analyse faciale en 3D sous un autre angle, en adoptant un système de cartes de représentation de la surface 3D. Nous avons ainsi proposé de projeter sur le plan 2D des informations liées à la topologie de la surface 3D, à l'aide d'un descripteur géométrique inspiré d'une mesure de courbure moyenne. Les problèmes de reconnaissance faciale et de reconnaissance d'expressions 3D sont alors ramenés à ceux de l'analyse faciale en 2D. Nous avons par exemple utilisé SIFT pour l'extraction puis l'appariement de points d'intérêt en reconnaissance faciale. En reconnaissance d'expressions, nous avons utilisé une méthode de description des visages basée sur les histogrammes de gradients orientés, puis classé les expressions à l'aide de SVM multi-classes. Dans les deux cas, une méthode de fusion simple permet l'agrégation des résultats obtenus à différentes échelles. Ces deux propositions ont été évaluées sur la base BU-3DFE, montrant de bonnes performances tout en étant complètement automatiques. Enfin, nous nous sommes intéressés à l'impact des dégradations des modèles 3D sur les performances des algorithmes d'analyse faciale. Ces dégradations peuvent avoir plusieurs origines, de la capture physique du visage humain au traitement des données en vue de leur interprétation par l'algorithme. Après une étude des origines et une théorisation des types de dégradations potentielles, nous avons défini une méthodologie permettant de chiffrer leur impact sur des algorithmes d'analyse faciale en 3D. Le principe est d'exploiter une base de données considérée sans défauts, puis de lui appliquer des dégradations canoniques et quantifiables. Les algorithmes d'analyse sont alors testés en comparaison sur les bases dégradées et originales. Nous avons ainsi comparé le comportement de 4 algorithmes de reconnaissance faciale en 3D, ainsi que leur fusion, en présence de dégradations, validant par la diversité des résultats obtenus la pertinence de ce type d'évaluation. / Historically and socially, the human face is one of the most natural modalities for determining the identity and the emotional state of a person. It has been exploited by computer vision scientists within the automatic facial analysis domain. Still, proposed algorithms classically encounter a number of shortcomings. They must be robust to varied acquisition conditions. Depending on the scenario, they must take into account intra-class variations such as expression, identity (for facial expression recognition), aging, occlusions. Thus, the 3D modality has been suggested as a counterpoint for a number of those issues. In principle, 3D views of an object are insensitive to lightning conditions. They are, theoretically, pose-independant as well. The present thesis work is dedicated to 3D Face Analysis. More precisely, it is focused on non-textured 3D Face Recognition and 3D Facial Expression Recognition. In the first instance, we have studied the benefits of a region-based approach to 3D Face Analysis problems. The general concept is that a face, when performing facial expressions, is deformed locally by the activation of muscles or groups of muscles. We then assumed that it was possible to decompose the face into several regions of interest, assumed to be either mimic or static. We have proposed a specific facial surface parametrization, based upon geodesic distance. It is designed to make region localization as robust as possible regarding expression variations. We have also used a region-based approach for 3D facial expression recognition, which allows us to compensate for errors relative to automatic landmark localization. We also wanted to experiment with a Representation Map system. Here, the main idea is to project 3D surface topology data on the 2D plan. This translation to the 2D domain allows us to benefit from the large amount of related works in the litterature. We first represent the face as a set of maps representing different scales, with the help of a geometric operator inspired by the Mean Curvature measure. For Facial Recognition, we perform a SIFT keypoints extraction. Then, we match extracted keypoints between corresponding maps. As for Facial Expression Recognition, we normalize and describe every map thanks to the Histograms of Oriented Gradients algorithm. We further classify expressions using multi-class SVM. In both cases, a simple fusion step allows us to aggregate the results obtained on every single map. Finally, we have studied the impact of 3D models degradations over the performances of 3D facial analysis algorithms. A 3D facial scan may be an altered representation of its real life model, because of several reasons, which range from the physical caption of the human model to data processing. We propose a methodology that allows us to quantify the impact of every single type of degradation over the performances of 3D face analysis algorithms. The principle is to build a database regarded as free of defaults, then to apply measurable degradations to it. Algorithms are further tested on clean and degraded datasets, which allows us to quantify the performance loss caused by degradations. As an experimental proof of concept, we have tested four different algorithms, as well as their fusion, following the aforementioned protocol. With respect to the various types of contemplated degradations, the diversity of observed behaviours shows the relevance of our approach.

This thesis deals with facial recognition using convolutional neural networks and with their current problems, which are pose, lighting and expression variance. It summarizes existing approaches, architectures and most recent loss functions. Further it deals with methods for rotating faces using GAN networks. In this thesis 3 neural networks are designed and trained for facial recognition. The best of them achieves 99.38% accuracy on LFW dataset and 88.08% accuracy on CPLFW dataset. Next face rotation network PCGAN is designed, which can be used for face frontalization or data augmentation purposes. This network is evaluated on Multi-PIE dataset and using the face frontalization it increases identification accuracy.

<p>This study examined how three different manipulations of a single policing stance affected the quality scores and matching performance in a biometric facial recognition system; it was conducted in three phases. In the first phase, the researcher collected qualitative survey data from active, sworn law enforcement officers in 15 states. In the second phase, the researcher collected quantitative data using a single facial recognition subject and a static body-worn camera mounted to an adjustable tripod. In the third phase, the researcher collected quantitative data from body-worn camera-equipped law enforcement officers who filmed a stationary target as they executed a series of specified movements from the interview stance. The second phase tested two different body-worn cameras: one that is popular among law enforcement agencies in the United States, the Axon Body 2; and one that is inexpensive and available to the general public via a popular internet commerce website. The third phase tested only the Axon Body 2. Results of the study showed that matching results are poor in a biometric system where the test body-worn camera was the sensor, with error rates as high as 100% when the body-worn camera wearer was in motion. The general conclusion of this study is that a body-worn camera is not a suitable sensor for a biometric facial recognition system at this time, though advances in camera technology and biometric systems may close the gap in the future. </p>

I en tid där digitaliseringen är mer utbredd än någonsin ökar också mängden data som samlas och delas online. I takt med att nya tekniker utvecklas öppnas det upp för nya utmaningar för integritetsfrågor. En aktiv användare online ägnar sig med största sannolikhet också åt ett eller flera sociala medier, där ändamålen ofta innebär att dela med sig av information till andra. Eftersom tekniken Augmented Reality används mer frekvent i några av de största sociala medieapplikationerna blev studiens syfte att undersöka potentiella integritetsproblem med Augmented Reality. Studiens tillvägagångssätt har bestått av en empirisk datainsamling för att skapa ett teoretiskt ramverk för studien. Utifrån detta har det genomförts en digital enkät samt intervjuer för att närmare undersöka användarens beteende online och The Privacy Paradox. Utifrån undersökningens resultat kunde The Privacy Paradox bekräftas och ge en bättre förståelse för hur användaren agerar genom digitala kanaler. I studien behandlas olika aspekter kring integritetsfrågor såsom användarvillkor, sekretessavtal, datamäklare, framtida konsekvenser och vad tekniken möjliggör. Studien kommer fram till att användare, företaget och dagens teknik tillåter att en känsligare information kan utvinnas genom ett dataintrång. Även om det ännu inte har inträffat ett dataintrång som grundat sig i Augmented Reality före denna studie, finns det en risk att det endast handlar om en tidsfråga innan detta sker. / In a time when digitalization is more widespread than ever, the amount of data collected and shared is increasing. As new technologies develop, challenges for privacy concerns arises. An active online user is likely to engage in one or many social media platforms, where the purpose often involves sharing information with others. Since Augmented Reality is more frequently supported in some of the biggest social media applications, the purpose of this study was to investigate potential privacy concerns with Augmented Reality. The study’s approach consisted of an empirical data collection to create a theoretical framework for the study. Based on this, a digital survey and interviews were conducted to further investigate the user's behavior online and The Privacy Paradox. Based on the results of the survey, The Privacy Paradox could be confirmed and a better understanding of how the user interacts through digital channels was achieved. The study treats different aspects of privacy concerns such as user terms, privacy policies, data brokers, future consequences and what technology enables. The study reached the conclusion that users, businesses and today's technology allow a more sensitive type of information to be collected through a data breach. Even if there has not yet occurred a data breach enabled by Augmented Reality prior to this study, there is a risk that it is only a matter of time until this happens.

El presente trabajo se basa en el diseño de un sistema de seguridad física, aplicando tecnología de reconocimiento facial, para el control de acceso en una empresa del sector minero, este sistema permite tener un control robusto y confiable de los usuarios que ingresan y transitan por el campamento minero, este sistema se adapta a la nueva realidad que estamos viviendo, donde el distanciamiento social, el contacto físico personal y la medición de la temperatura, es un requisito indispensable. El diseño propuesto toma como referencia las mejores prácticas de las normas IEC 80601-2-59:2017 e ISO/TR 13154:2017, así como las recomendaciones del NISTIR 8238 que nos habla sobre la prueba continua de proveedores de reconocimiento facial. La problemática actual, es con referencia a la desactualización tecnología que tienen casi el 90% de los sistemas de seguridad de las empresas del sector minero, ya que, tras la llegada de la pandemia, estos sistemas se vieron evidenciados del pobre avance tecnológico con el que contaban. El diseño propuesto integra el uso de algoritmos con inteligencia artificial que permiten automatizar el proceso de identificación de los usuarios a través de su rostro, utilizando el flujo de video de las cámaras, analizamos la cobertura de las áreas a cubrir a través de los cálculos ópticos y distancia focal de las cámaras, proponemos también un mecanismo de gestión y tratamiento de las alertas que se generen de las analíticas aplicadas. Finalmente realizamos una comprobación y evidenciamos los resultados del diseño para cada objetivo específico planteado. / This work is based on the design of a physical security system, applying facial recognition technology, for access control in a company in the mining sector, this system allows to have a robust and reliable control of users entering and passing through the mining camp, this system adapts to the new reality we are living, where social distancing, personal physical contact, and temperature measurement, are indispensable requirements. The proposed design takes as a reference the best practices of the IEC 80601-2-59:2017 and ISO/TR 13154:2017 standards, as well as the recommendations of the NISTIR 8238 that tells us about the continuous testing of facial recognition providers. The current problem is related to the technological outdatedness of almost 90% of the security systems of the companies in the mining sector, since, after the arrival of the pandemic, these systems were evidenced by the poor technological progress they had. The proposed design integrates the use of algorithms with artificial intelligence that allow us to automate the process of identifying users through their face, using the video flow of the cameras, we analyse the coverage of the areas to be covered through optical calculations and focal length of the cameras, we also propose a mechanism for the management and treatment of alerts generated from applied analytics. Finally, we verify and show the results of the design for each specific objective set previously. / Tesis

La capacité à reconnaître les visages de nos collègues, de nos amis et de nos proches est essentielle à notre réussite en tant qu'êtres sociaux. Notre cerveau accomplit cet exploit facilement et rapidement, dans une série d’opérations se déroulant en quelques dizaines de millisecondes à travers un vaste réseau cérébral du système visuel ventral. L’habileté à reconnaître les visages, par contre, varie considérablement d’une personne à l’autre. Certains individus, appelés «super-recognisers», sont capables de reconnaître des visages vus une seule fois dans la rue des années plus tôt. D’autres, appelés «prosopagnosiques», sont incapables de reconnaître le visage de leurs collègues ou leurs proches, même avec une vision parfaite. Une question simple reste encore largement sans réponse : quels mécanismes expliquent que certains individus sont meilleurs à reconnaître des visages? Cette thèse rapporte cinq articles étudiant les mécanismes perceptifs (articles 1, 2, 3) et cérébraux (articles 4, 5) derrière ces variations à travers différentes populations d’individus. L’article 1 décrit le contenu des représentations visuelles faciales chez une population avec un diagnostic de schizophrénie et d’anxiété sociale à l’aide d’une technique psychophysique Bubbles. Nous révélons pour la première fois les mécanismes en reconnaissance des expressions de cette population: un déficit de reconnaissance est accompagné par i) une sous-utilisation de la région des yeux des visages expressifs et ii) une sous-utilisation des détails fins. L’article 2 valide ensuite une nouvelle technique permettant de révéler simultanément le contenu visuel dans trois dimensions psychophysiques centrales pour le système visuel — la position, les fréquences spatiales, et l’orientation. L’article 3 a mesuré, à l'aide de cette nouvelle technique, le contenu représentationnel de 120 individus pendant la discrimination faciale du sexe et des expressions ( >500,000 observations). Nous avons observé de fortes corrélations entre l’habileté à discriminer le sexe et les expressions des visages, ainsi qu'entre l’habileté à discriminer le sexe et l’identité. Crucialement, plus un individu est habile en reconnaissance faciale, plus il utilise un contenu représentationnel similaire entre les tâches. L’article 4 a examiné les computations cérébrales de super-recognisers en utilisant l’électroencéphalographie haute-densité (EEG) et l’apprentissage automatique. Ces outils ont permis de décoder, pour la première fois, l’habileté en reconnaissance faciale à partir du cerveau avec jusqu’à 80% d’exactitude –– et ce à partir d’une seule seconde d’activité cérébrale. Nous avons ensuite utilisé la Representational Similarity Analysis (RSA) pour comparer les représentations cérébrales de nos participants à celles de modèles d’apprentissage profond visuels et langagiers. Les super-recognisers, comparé aux individus avec une habileté typique, ont des représentations cérébrales plus similaires aux computations visuelles et sémantiques de ces modèles optimaux. L’article 5 rapporte une investigation des computations cérébrales chez le cas le plus spécifique et documenté de prosopagnosie acquise, la patiente PS. Les mêmes outils computationnels et d’imagerie que ceux de l’article 4 ont permis i) de décoder les déficits d’identification faciale de PS à partir de son activité cérébrale EEG, et ii) de montrer pour la première fois que la prosopagnosie est associée à un déficit des computations visuelles de haut niveau et des computations cérébrales sémantiques. / The ability to recognise the faces of our colleagues, friends, and family members is critical to our success as social beings. Our brains accomplish this feat with astonishing ease and speed, in a series of operations taking place in tens of milliseconds across a vast brain network of the visual system. The ability to recognise faces, however, varies considerably from one person to another. Some individuals, called "super-recognisers", are able to recognise faces seen only once years earlier. Others, called "prosopagnosics", are unable to recognise the faces of their colleagues or relatives, even with perfect vision and typical intelligence. A simple question remains largely unanswered: what mechanisms explain why some individuals are better at recognizing faces? This thesis reports five articles studying the perceptual (article 1, 2, 3) and neural (article 4, 5) mechanisms behind these variations across different populations of individuals. Article 1 describes the content of visual representations of faces in a population with a comorbid diagnosis of schizophrenia and social anxiety disorder using an established psychophysical technique, Bubbles. We reveal for the first time the perceptual mechanisms of expression recognition in this population: a recognition deficit is accompanied by i) an underutilization of the eye region of expressive faces and ii) an underutilization of fine details. Article 2 then validates a new psychophysical technique that simultaneously reveals the visual content in three dimensions central to the visual system — position, spatial frequencies, and orientation. We do not know, however, whether skilled individuals perform well across a variety of facial recognition tasks and, if so, how they accomplish this feat. Article 3 measured, using the technique validated in article 2, the perceptual representations of 120 individuals during facial discrimination of gender and expressions (total of >500,000 trials). We observed strong correlations between the ability to discriminate gender and facial expressions, as well as between the ability to discriminate gender and identify faces. More importantly, we found a positive correlation between individual ability and the similarity of perceptual representations used across these tasks. Article 4 examined differences in brain dynamics between super-recognizers and typical individuals using high-density electroencephalography (EEG) and machine learning. These tools allowed us to decode, for the first time, facial recognition ability from the brain with up to 80% accuracy — using a mere second of brain activity. We then used Representational Similarity Analysis (RSA) to compare our participants' brain representations to those of deep learning models of object and language classification. This showed that super-recognisers, compared to individuals with typical perceptual abilites, had brain representations more similar to the visual and semantic computations of these optimal models. Article 5 reports an investigation of brain computations in the most specific and documented case of acquired prosopagnosia, patient PS. The same computational tools used in article 4 enabled us to decode PS's facial identification deficits from her brain dynamics. Crucially, associations between brain deep learning models showed for the first time that prosopagnosia is associated with deficits in high-level visual and semantic brain computations.