Letteratura scientifica selezionata sul tema "Reconnaissance faciale (Informatique)"
Cita una fonte nei formati APA, MLA, Chicago, Harvard e in molti altri stili
Consulta la lista di attuali articoli, libri, tesi, atti di convegni e altre fonti scientifiche attinenti al tema "Reconnaissance faciale (Informatique)".
Accanto a ogni fonte nell'elenco di riferimenti c'è un pulsante "Aggiungi alla bibliografia". Premilo e genereremo automaticamente la citazione bibliografica dell'opera scelta nello stile citazionale di cui hai bisogno: APA, MLA, Harvard, Chicago, Vancouver ecc.
Puoi anche scaricare il testo completo della pubblicazione scientifica nel formato .pdf e leggere online l'abstract (il sommario) dell'opera se è presente nei metadati.
Tesi sul tema "Reconnaissance faciale (Informatique)"
Kose, Neslihan. "Leurrage et dissimulation en reconnaissance faciale : analyses et contre attaques". Electronic Thesis or Diss., Paris, ENST, 2014. http://www.theses.fr/2014ENST0020.
Testo completoHuman recognition has become an important topic as the need and investments for security applications grow continuously. Numerous biometric systems exist which utilize various human characteristics. Among all biometrics traits, face recognition is advantageous in terms of accessibility and reliability. In the thesis, two challenges in face recognition are analyzed. The first one is face spoofing. Spoofing in face recognition is explained together with the countermeasure techniques that are proposed for the protection of face recognition systems against spoofing attacks. For this purpose, both 2D photograph and 3D mask attacks are analyzed. The second challenge explored in the thesis is disguise variations, which are due to facial alterations, facial makeup and facial accessories (occlusions). The impact of these disguise variations on face recognition is explored, separately. Then, techniques which are robust against disguise variations are proposed
Kose, Neslihan. "Leurrage et dissimulation en reconnaissance faciale : analyses et contre attaques". Thesis, Paris, ENST, 2014. http://www.theses.fr/2014ENST0020/document.
Testo completoHuman recognition has become an important topic as the need and investments for security applications grow continuously. Numerous biometric systems exist which utilize various human characteristics. Among all biometrics traits, face recognition is advantageous in terms of accessibility and reliability. In the thesis, two challenges in face recognition are analyzed. The first one is face spoofing. Spoofing in face recognition is explained together with the countermeasure techniques that are proposed for the protection of face recognition systems against spoofing attacks. For this purpose, both 2D photograph and 3D mask attacks are analyzed. The second challenge explored in the thesis is disguise variations, which are due to facial alterations, facial makeup and facial accessories (occlusions). The impact of these disguise variations on face recognition is explored, separately. Then, techniques which are robust against disguise variations are proposed
Abdat, Faiza. "Reconnaissance automatique des émotions par données multimodales : expressions faciales et des signaux physiologiques". Electronic Thesis or Diss., Metz, 2010. http://www.theses.fr/2010METZ035S.
Testo completoThis thesis presents a generic method for automatic recognition of emotions from a bimodal system based on facial expressions and physiological signals. This data processing approach leads to better extraction of information and is more reliable than single modality. The proposed algorithm for facial expression recognition is based on the distance variation of facial muscles from the neutral state and on the classification by means of Support Vector Machines (SVM). And the emotion recognition from physiological signals is based on the classification of statistical parameters by the same classifier. In order to have a more reliable recognition system, we have combined the facial expressions and physiological signals. The direct combination of such information is not trivial giving the differences of characteristics (such as frequency, amplitude, variation, and dimensionality). To remedy this, we have merged the information at different levels of implementation. At feature-level fusion, we have tested the mutual information approach for selecting the most relevant and principal component analysis to reduce their dimensionality. For decision-level fusion we have implemented two methods; the first based on voting process and another based on dynamic Bayesian networks. The optimal results were obtained with the fusion of features based on Principal Component Analysis. These methods have been tested on a database developed in our laboratory from healthy subjects and inducing with IAPS pictures. A self-assessment step has been applied to all subjects in order to improve the annotation of images used for induction. The obtained results have shown good performance even in presence of variability among individuals and the emotional state variability for several days
Abdat, Faiza. "Reconnaissance automatique des émotions par données multimodales : expressions faciales et des signaux physiologiques". Thesis, Metz, 2010. http://www.theses.fr/2010METZ035S/document.
Testo completoThis thesis presents a generic method for automatic recognition of emotions from a bimodal system based on facial expressions and physiological signals. This data processing approach leads to better extraction of information and is more reliable than single modality. The proposed algorithm for facial expression recognition is based on the distance variation of facial muscles from the neutral state and on the classification by means of Support Vector Machines (SVM). And the emotion recognition from physiological signals is based on the classification of statistical parameters by the same classifier. In order to have a more reliable recognition system, we have combined the facial expressions and physiological signals. The direct combination of such information is not trivial giving the differences of characteristics (such as frequency, amplitude, variation, and dimensionality). To remedy this, we have merged the information at different levels of implementation. At feature-level fusion, we have tested the mutual information approach for selecting the most relevant and principal component analysis to reduce their dimensionality. For decision-level fusion we have implemented two methods; the first based on voting process and another based on dynamic Bayesian networks. The optimal results were obtained with the fusion of features based on Principal Component Analysis. These methods have been tested on a database developed in our laboratory from healthy subjects and inducing with IAPS pictures. A self-assessment step has been applied to all subjects in order to improve the annotation of images used for induction. The obtained results have shown good performance even in presence of variability among individuals and the emotional state variability for several days
Le, Meur Julien. "Conception, assemblage, optimisation et test de modules intégrés d'illumination structurée à base d'éléments optiques diffractifs : application particulière à la reconnaissance faciale". Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2018. http://www.theses.fr/2018IMTA0121.
Testo completoThis thesis work aimed to design, assemble, optimize and test structured illumination modules based on diffractive optical elements (DOEs) for facial recognition application on mobile devices (smartphones, tablets). The integration of modules into smartphones involved significant constraints in terms of miniaturization, energy consumption, cost and laser safety. The key element of each module was a Fourier DOE with a diffraction angle greater than the limit of the paraxial scalar diffraction model to illuminate the surface of a face at a distance of an arm reach. In order to facilitate the design (relaxation of angular constraints), manufacturing (minimization of the zero order diffraction efficiency) and replication of DOEs, the first axis of research consisted in designing and manufacturing hybrid "angle enlarger" devices combining DOEs and conventional divergent optics. The second part concerned the design of the DOEs, which had to take into account both the parameters of the low-cost illumination and image acquisition systems used, in particular to control the presence of laser speckle on the desired diffraction pattern (control imposed by the facial recognition and fraud detection algorithms used). The know-how acquired in the field of structured illumination generated by DOEs has been extended and transposed to three other applications in the fields of vibrometry, civil and commercial aviation, and military aviation
Deramgozin, Mohammadmahdi. "Développement de modèles de reconnaissance des expressions faciales à base d’apprentissage profond pour les applications embarquées". Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0286.
Testo completoThe field of Facial Emotion Recognition (FER) is pivotal in advancing human-machine interactions and finds essential applications in healthcare for conditions like depression and anxiety. Leveraging Convolutional Neural Networks (CNNs), this thesis presents a progression of models aimed at optimizing emotion detection and interpretation. The initial model is resource-frugal but competes favorably with state-of-the-art solutions, making it a strong candidate for embedded systems constrained in computational and memory resources. To capture the complexity and ambiguity of human emotions, the research work presented in this thesis enhances this CNN-based foundational model by incorporating facial Action Units (AUs). This approach not only refines emotion detection but also provides interpretability by identifying specific AUs tied to each emotion. Further sophistication is achieved by introducing neural attention mechanisms—both spatial and channel-based—improving the model's focus on salient facial features. This makes the CNN-based model adapted well to real-world scenarios, such as partially obscured or subtle facial expressions. Based on the previous results, in this thesis we propose finally an optimized, yet computationally efficient, CNN model that is ideal for resource-limited environments like embedded systems. While it provides a robust solution for FER, this research also identifies perspectives for future work, such as real-time applications and advanced techniques for model interpretability
Ballihi, Lahoucine. "Biométrie faciale 3D par apprentissage des caractéristiques géométriques : Application à la reconnaissance des visages et à la classification du genre". Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2012. http://tel.archives-ouvertes.fr/tel-00726299.
Testo completoAl, chanti Dawood. "Analyse Automatique des Macro et Micro Expressions Faciales : Détection et Reconnaissance par Machine Learning". Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT058.
Testo completoFacial expression analysis is an important problem in many biometric tasks, such as face recognition, face animation, affective computing and human computer interface. In this thesis, we aim at analyzing facial expressions of a face using images and video sequences. We divided the problem into three leading parts.First, we study Macro Facial Expressions for Emotion Recognition and we propose three different levels of feature representations. Low-level feature through a Bag of Visual Word model, mid-level feature through Sparse Representation and hierarchical features through a Deep Learning based method. The objective of doing this is to find the most effective and efficient representation that contains distinctive information of expressions and that overcomes various challenges coming from: 1) intrinsic factors such as appearance and expressiveness variability and 2) extrinsic factors such as illumination, pose, scale and imaging parameters, e.g., resolution, focus, imaging, noise. Then, we incorporate the time dimension to extract spatio-temporal features with the objective to describe subtle feature deformations to discriminate ambiguous classes.Second, we direct our research toward transfer learning, where we aim at Adapting Facial Expression Category Models to New Domains and Tasks. Thus we study domain adaptation and zero shot learning for developing a method that solves the two tasks jointly. Our method is suitable for unlabelled target datasets coming from different data distributions than the source domain and for unlabelled target datasets with different label distributions but sharing the same context as the source domain. Therefore, to permit knowledge transfer between domains and tasks, we use Euclidean learning and Convolutional Neural Networks to design a mapping function that map the visual information coming from facial expressions into a semantic space coming from a Natural Language model that encodes the visual attribute description or use the label information. The consistency between the two subspaces is maximized by aligning them using the visual feature distribution.Third, we study Micro Facial Expression Detection. We propose an algorithm to spot micro-expression segments including the onset and offset frames and to spatially pinpoint in each image space the regions involved in the micro-facial muscle movements. The problem is formulated into Anomaly Detection due to the fact that micro-expressions occur infrequently and thus leading to few data generation compared to natural facial behaviours. In this manner, first, we propose a deep Recurrent Convolutional Auto-Encoder to capture spatial and motion feature changes of natural facial behaviours. Then, a statistical based model for estimating the probability density function of normal facial behaviours while associating a discriminating score to spot micro-expressions is learned based on a Gaussian Mixture Model. Finally, an adaptive thresholding technique for identifying micro expressions from natural facial behaviour is proposed.Our algorithms are tested over deliberate and spontaneous facial expression benchmarks
Huang, Di. "Robust face recognition based on three dimensional data". Phd thesis, Ecole Centrale de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00693158.
Testo completoBen, Soltana Wael. "Optimisation de stratégies de fusion pour la reconnaissance de visages 3D". Phd thesis, Ecole Centrale de Lyon, 2012. http://tel.archives-ouvertes.fr/tel-01070638.
Testo completoLibri sul tema "Reconnaissance faciale (Informatique)"
W, Vorder Bruegge Richard, a cura di. Computer-aided forensic facial comparison. Boca Raton, FL: Taylor & Francis Group, 2010.
Cerca il testo completoJr, Woodward John D., Virginia State Crime Commission e Rand Corporation, a cura di. Biometrics: A look at facial recognition. Santa Monica, Calif: RAND, 2003.
Cerca il testo completo1959-, Pugliese Joseph, a cura di. Biometrics: Bodies, technologies, biopolitics. New York: Routledge, 2010.
Cerca il testo completoEvison, Martin Paul, e Richard W. Vorder Bruegge. Computer-Aided Forensic Facial Comparison. Taylor & Francis Group, 2010.
Cerca il testo completoDatta, Asit Kumar, Madhura Datta e Pradipta Kumar Banerjee. Face Detection and Recognition: Theory and Practice. Taylor & Francis Group, 2015.
Cerca il testo completoDatta, Asit Kumar, Madhura Datta e Pradipta Kumar Banerjee. Face Detection and Recognition. Taylor & Francis Group, 2019.
Cerca il testo completoauthor, Datta Madhura, e Banerjee Pradipta Kumar author, a cura di. Face detection and recognition: Theory and practice. CRC Press/Taylor & Francis Group, 2016.
Cerca il testo completoCognitive and Computational Aspects of Face Recognition: Explorations in Face Space. Taylor & Francis Group, 2017.
Cerca il testo completoCognitive and Computational Aspects of Face Recognition: Explorations in Face Space. Taylor & Francis Group, 2017.
Cerca il testo completoCognitive and Computational Aspects of Face Recognition: Explorations in Face Space. Routledge, 1995.
Cerca il testo completo