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Academic literature on the topic 'Reconnaissance de gestes en temps réel'
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Journal articles on the topic "Reconnaissance de gestes en temps réel"
Abdat, F., C. Maaoui, and Alain Pruski. "Reconnaissance d'expressions faciales en temps réel à partir d'une séquence vidéo." Sciences et Technologies pour le Handicap 3, no. 1 (June 30, 2009): 63–93. http://dx.doi.org/10.3166/sth.3.63-93.
Full textCont, Arshia. "Modélisation anticipative des systèmes musicaux. Reconnaissance, génération, synchronisation et programmation synchrone temps réel en informatique musicale." Techniques et sciences informatiques 31, no. 3 (March 30, 2012): 311–35. http://dx.doi.org/10.3166/tsi.31.311-335.
Full textLasserre, Evelyne, Axel Guïoux, and Jérôme Goffette. "Dynamiques ludiques." Anthropologie et Sociétés 35, no. 1-2 (November 2, 2011): 129–46. http://dx.doi.org/10.7202/1006372ar.
Full textRebillard, C., A. Lambrechts, B. Guillery-Girard, F. Eustache, J. M. Baleyte, J. Spiess, and K. Lebreton. "Apport de la technique d’Eye-tracking dans la compréhension de l’impact des particularités perceptives sur la cognition dans les Troubles du Spectre Autistique (TSA)." European Psychiatry 29, S3 (November 2014): 598. http://dx.doi.org/10.1016/j.eurpsy.2014.09.194.
Full textCharles, D. "L’interne en psychiatrie face au risque juridique : quels aspects pratiques ?" European Psychiatry 29, S3 (November 2014): 634. http://dx.doi.org/10.1016/j.eurpsy.2014.09.146.
Full textKouame, KL, AB Yao, and KI N'Dri. "Etat des lieux de la pandémie de COVID-19 en Côte d'Ivoire." Revue Malienne d'Infectiologie et de Microbiologie 16, no. 1 (January 31, 2021): 54–60. http://dx.doi.org/10.53597/remim.v16i1.1771.
Full textKilani, Mondher. "Identité." Anthropen, 2019. http://dx.doi.org/10.17184/eac.anthropen.122.
Full textMartin, Brigitte. "Cosmopolitisme." Anthropen, 2019. http://dx.doi.org/10.17184/eac.anthropen.120.
Full textDissertations / Theses on the topic "Reconnaissance de gestes en temps réel"
Barnachon, Mathieu. "Reconnaissance d'actions en temps réel à partir d'exemples." Phd thesis, Université Claude Bernard - Lyon I, 2013. http://tel.archives-ouvertes.fr/tel-00820113.
Full textCoupeté, Eva. "Reconnaissance de gestes et actions pour la collaboration homme-robot sur chaîne de montage." Thesis, Paris Sciences et Lettres (ComUE), 2016. http://www.theses.fr/2016PSLEM062/document.
Full textCollaborative robots are becoming more and more present in our everyday life. In particular, within the industrial environment, they emerge as one of the preferred solution to make assembly line in factories more flexible, cost-effective and to reduce the hardship of the operators’ work. However, to enable a smooth and efficient collaboration, robots should be able to understand their environment and in particular the actions of the humans around them.With this aim in mind, we decided to study technical gestures recognition. Specifically, we want the robot to be able to synchronize, adapt its speed and understand if something unexpected arises.We considered two use-cases, one dealing with copresence, the other with collaboration. They are both inspired by existing task on automotive assembly lines.First, for the co-presence use case, we evaluated the feasibility of technical gestures recognition using inertial sensors. We obtained a very good result (96% of correct recognition with one operator) which encouraged us to follow this idea.On the collaborative use-case, we decided to focus on non-intrusive sensors to minimize the disturbance for the operators and we chose to use a depth-camera. We filmed the operators with a top view to prevent most of the potential occultations.We introduce an algorithm that tracks the operator’s hands by calculating the geodesic distances between the points of the upper body and the top of the head.We also design and evaluate an approach based on discrete Hidden Markov Models (HMM) taking the hand positions as an input to recognize technical gestures. We propose a method to adapt our system to new operators and we embedded inertial sensors on tools to refine our results. We obtain the very good result of 90% of correct recognition in real time for 13 operators.Finally, we formalize and detail a complete methodology to realize technical gestures recognition on assembly lines
Cassel, Ryan. "Analyse du mouvement humain par un système de vision : une approche globale pour l'analyse et la reconnaissance en temps réel de mouvements acrobatiques." Paris 11, 2005. http://www.theses.fr/2005PA112282.
Full textAcrobatics is an area of athletics that is exacting in terms of gesture analysis and recognition. It comprises body rotations along two separate axes that result in fast and complex movements. Acrobatics intervene in multiple disciplines such as gymnastics, trampoline, ski, and diving. Devices for capturing movements based on markers and multiple cameras for movement analysis are problematic to implement in the context of training and are not exploitable in competition. A single camera may be used but the movement's complexity makes it very difficult to use traditional machine vision techniques without markers to carry out the analysis. Our approach offers a monocular system of analysis and recognition of acrobatic movements in real time, based on global measurements. Information relating to the acrobat's movements-without identifying specific body parts-constitutes our global measurements. Thus, we have developed movement models based on acrobatics characteristics and on global measurements extracted from image sequences. Moreover, we present a system capable of analyzing acrobatic movements with a view toward improvements of athletic performance, or for identifying the performance level of an acrobat. Analysis and recognition are based on measures of the movements identified by extracting and tracking the acrobat
Granger, Nicolas. "Deep-learning for high dimensional sequential observations : application to continuous gesture recognition." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL002/document.
Full textThis thesis aims to improve the intuitiveness of human-computer interfaces. In particular, machines should try to replicate human's ability to process streams of information continuously. However, the sub-domain of Machine Learning dedicated to recognition on time series remains barred by numerous challenges. Our studies use gesture recognition as an exemplar application, gestures intermix static body poses and movements in a complex manner using widely different modalities. The first part of our work compares two state-of-the-art temporal models for continuous sequence recognition, namely Hybrid Neural Network--Hidden Markov Models (NN-HMM) and Bidirectional Recurrent Neural Networks (BDRNN) with gated units. To do so, we reimplemented the two within a shared test-bed which is more amenable to a fair comparative work. We propose adjustments to Neural Network training losses and the Hybrid NN-HMM expressions to accommodate for highly imbalanced data classes. Although recent publications tend to prefer BDRNNs, we demonstrate that Hybrid NN-HMM remain competitive. However, the latter rely significantly on their input layers to model short-term patterns. Finally, we show that input representations learned via both approaches are largely inter-compatible. The second part of our work studies one-shot learning, which has received relatively little attention so far, in particular for sequential inputs such as gestures. We propose a model built around a Bidirectional Recurrent Neural Network. Its effectiveness is demonstrated on the recognition of isolated gestures from a sign language lexicon. We propose several improvements over this baseline by drawing inspiration from related works and evaluate their performances, exhibiting different advantages and disadvantages for each
Poupet, Victor. "Automates cellulaires : temps réel et voisinages." Lyon, École normale supérieure (sciences), 2006. http://www.theses.fr/2006ENSL0390.
Full textIn this thesis we have worked on the impact of the choice of a neighborhood on the algorithmic abilities of cellular automata. We have specifically studied the lower complexity classes such as the real time (that corresponds to the shortest time necessary for a cellular automaton to read all the letters of the input word) and the real time plus a constant. It is indeed known that neighborhoods are equivalent in linear time and it is therefore necessary to consider shorter times. We have obtained neighborhood equivalence results with respect to the real time (neighborhood classes such that cellular automata working on any of those neighborhoods can recognize the same languages in real time) and linear or constant speed-up theorems for many classes of neighborhoods
Grandjean, Anaël. "Reconnaissance de langage en temps réel sur automates cellulaires 2D." Thesis, Montpellier, 2016. http://www.theses.fr/2016MONTT331/document.
Full textCellular automata were introduced in the 50s by J. von Neumann and S. Ulamas an efficient way of modeling massively parallel computation. Many variations of the model can be considered such as varying the dimension of the computation space or the communication capabilities of the computing cells. In a cellular automaton each cell can communicate only with a finite number of other cells called its neighbors. My work focuses on the impact of the choice of the neighbors on the algorithmic properties of the model. My first goal was to generalize some classical properties of computation models to the widest possible class of neighborhoods, in particular I prove a linear speedup theorem for any two dimensional neighborhood. I then study the difference between the complexity classes defined by different neighborhoods, show the existence of neighborhoods defining incomparable classes, and some sets of neighborhoods defining identical classes. Finally, I also discuss the impact of the dimension of the automata on their computational power
Malasné, Nicolas. "Localisation et reconnaissance de visages en temps réel : algorithmes et architectures." Dijon, 2002. http://www.theses.fr/2002DIJOS045.
Full textBorello, Alex. "Reconnaissance de langages en temps réel par des automates cellulaires avec contraintes." Thesis, Aix-Marseille 1, 2011. http://www.theses.fr/2011AIX10127.
Full textThis document deals with cellular automata as a model of computation used to recognise languages. In such a domain, it is always difficult to provide negative results, that is, typically, to prove that a given language is not recognised in some function of time by some class of automata. The document focuses in particular on the low-complexity classes such as real time, about which a lot of questions remain open since several decades.In a first part, several techniques to weaken further still these classes of languages are investigated, thereby bringing examples of negative results. A second part is dedicated to the comparison of cellular automata with another model language recognition, namely multi-head finite automata. This leads to speed-up theorem when finite automata are oblivious, which makes them a priori weaker than in the general case but leaves them a nontrivial power
Lahaye, Jean-Claude. "Etude et réalisation d'un système de vision temps réel par reconnaissance d'éléments rectilignes." Grenoble INPG, 1986. http://www.theses.fr/1986INPG0129.
Full textMénier, Clément. "Système de vision temps-réel pour les intéractions." Grenoble INPG, 2007. http://www.theses.fr/2007INPG0041.
Full textThis thesis focuses on the the real time acquisition of 3D information on a scene from multiple camera in the context of interactive applications. A complete vision system from image acquisition to motion and shape modeling is presented. The distribution of tasks on a PC cluster, and more precisely the parallelization of different shape modeling algorithms, enables a real time execution with a low latency. Several applications are developped and validate the practical implementation of this system. An original approach of motion modeling is lso presented. It allows for limbs tracking and identification white not requiring prior information on the shape of the user
Books on the topic "Reconnaissance de gestes en temps réel"
Robert, Pascal, ed. L'impensé numérique - Tome 2 - Interprétations critiques et logiques pragmatiques de l’impensé. Editions des archives contemporaines, 2020. http://dx.doi.org/10.17184/eac.9782813003577.
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