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Academic literature on the topic 'Segmentation d'objets en mouvement'
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Journal articles on the topic "Segmentation d'objets en mouvement"
Mazouzi, Smaine, Zahia Guessoum, and Fabien Michel. "Une approche multi-agent pour la segmentation d'images de profondeur à base d'objets polyédriques. Une nouvelle approche de segmentation d'images." Techniques et sciences informatiques 28, no. 3 (March 30, 2009): 365–93. http://dx.doi.org/10.3166/tsi.28.365-393.
Full textGademer, Antoine, Loïca Avanthey, Laurent Beaudouin, Michel Roux, and Jean-Paul Rudant. "Micro-charges utiles dédiées à l'acquisition de données par drone pour l'étude des zones naturelles." Revue Française de Photogrammétrie et de Télédétection, no. 213 (March 31, 2017): 19–31. http://dx.doi.org/10.52638/rfpt.2017.192.
Full textPignon, Lucas, Ludovic Delporte, Mathilde Duboisset, Gilles Rode, and Sébastien Mateo. "Accélérer atténue la segmentation du mouvement chez les patients souffrant d’ataxie génétique dégénérative : une étude cinématique." Kinésithérapie, la Revue 23, no. 255 (March 2023): 57. http://dx.doi.org/10.1016/j.kine.2022.12.100.
Full textSchlupp, Antoine, Georges Clauzon, and Jean-Philippe Avouac. "Mouvement post-messinien sur la faille de Nimes; implications pour la sismotectonique de la Provence." Bulletin de la Société Géologique de France 172, no. 6 (November 1, 2001): 697–711. http://dx.doi.org/10.2113/172.6.697.
Full textBARRIER, GUY. "Expansivité gestuelle et graphique: Problèmes et perspectives de la segmentation du mouvement expressif." Semiotica 123, no. 1-2 (1999). http://dx.doi.org/10.1515/semi.1999.123.1-2.31.
Full textBéchacq, Dimitri, and Hadrien Munier. "Vodou." Anthropen, 2016. http://dx.doi.org/10.17184/eac.anthropen.040.
Full textKilani-schoch, Marianne. "Langue et culture." Anthropen, 2016. http://dx.doi.org/10.17184/eac.anthropen.017.
Full textGagnon, Éric. "Âgisme." Anthropen, 2019. http://dx.doi.org/10.17184/eac.anthropen.089.
Full textDissertations / Theses on the topic "Segmentation d'objets en mouvement"
Devevey, Christophe. "Etude du mouvement sur des séquences d'images échographiques : : poursuite de cibles rigides et segmentation, par une approche connexionniste du champ, des vitesses d'objets déformables." Lyon, INSA, 1993. http://www.theses.fr/1993ISAL0006.
Full textThe purpose of this study is the exploitation of the motion information generated in ultrasonic image sequence. In the first section, the performances of four tracking techniques is first compared in terms of accuracy and processing time. The best algorithm. Based on correlation is then used to track gallstones or urinary stones in order to enhance the efficiency of extracorporeal lithotripsy. In the second part of this work. The optical flow is estimated and parametrized using two neural networks. The classification of the vector field parameters by clustering is then used for motion segmentation. The computer analysis of heart motion from two-dimensional echocardiograms using this technique can facilitate the diagnosis of cardiac pathology
Bonnaud, Laurent. "Schémas de suivi d'objets vidéo dans une séquence animée : application à l'interpolation d'images intermédiaires." Phd thesis, Université Rennes 1, 1998. http://tel.archives-ouvertes.fr/tel-00070533.
Full textaux séquences d'images, pour des applications multimédia. Ce travail est
divisé en deux contributions principales~: un algorithme de segmentation
d'images en objets vidéo en mouvement, et une méthode d'interpolation
temporelle opérant sur ces objets.
La segmentation de la séquence est effectuée par un algorithme de suivi
temporel. Un algorithme de segmentation spatio-temporelle est utilisé
initialement pour obtenir des régions dans la première image de la séquence.
Cette partition est ensuite suivie par une technique de contours actifs, qui
opère sur une nouvelle représentation de la segmentation, composée des
frontières ouvertes séparant les régions. L'algorithme estime à la fois le
mouvement des frontières et celui des régions. Il est capable de suivre
plusieurs objets simultanément et de traiter les occultations entre eux. Des
résultats, obtenus sur des séquences d'images réelles, montrent que cet
algorithme permet une bonne stabilité temporelle de la segmentation et une
bonne précision des frontières.
Le but de l'algorithme d'interpolation est de reconstruire des images
intermédiaires entre deux images de la séquence. Il s'agit d'un algorithme de
faible complexité qui peut être utilisé à la fin d'une chaîne codeur/décodeur.
L'interpolation est compensée en mouvement et utilise le mouvement des régions,
estimé pendant la phase de suivi. Il est aussi basé objets, dans le sens où il
utilise la segmentation pour prédire correctement les zones d'occultation. Cet
algorithme peut être utilisé pour trois applications différentes~: le codage
interpolatif (où des images de la séquence sont prédites par interpolation),
l'adaptation de la fréquence de la séquence à la fréquence d'affichage du
terminal de visualisation dans une transmission multipoints et la
reconstruction d'images manquantes (où l'on calcule des images non observées).
Des résultats expérimentaux pour la première application montrent que pour une
qualité de reconstruction donnée, la taux de compression moyen sur un groupe
d'images est plus élevé en utilisant l'interpolation qu'avec une prédiction
causale.
Pérez, Rúa Juan Manuel. "Hierarchical motion-based video analysis with applications to video post-production." Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S125/document.
Full textThe manuscript that is presented here contains all the findings and conclusions of the carried research in dynamic visual scene analysis. To be precise, we consider the ubiquitous monocular camera computer vision set-up, and the natural unconstrained videos that can be produced by it. In particular, we focus on important problems that are of general interest for the computer vision literature, and of special interest for the film industry, in the context of the video post-production pipeline. The tackled problems can be grouped in two main categories, according to the whether they are driven user interaction or not : user-assisted video processing tools and unsupervised tools for video analysis. This division is rather synthetic but it is in fact related to the ways the proposed methods are used inside the video post-production pipeline. These groups correspond to the main parts that form this manuscript, which are subsequently formed by chapters that explain our proposed methods. However, a single thread ties together all of our findings. This is, a hierarchical analysis of motion composition in dynamic scenes. We explain our exact contributions, together with our main motivations, and results in the following sections. We depart from a hypothesis that links the ability to consider a hierarchical structure of scene motion, with a deeper level of dynamic scene understanding. This hypothesis is inspired by plethora of scientific research in biological and psychological vision. More specifically, we refer to the biological vision research that established the presence of motion-related sensory units in the visual cortex. The discovery of these specialized brain units motivated psychological vision researchers to investigate how animal locomotion (obstacle avoidance, path planning, self-localization) and other higher-level tasks are directly influenced by motion-related percepts. Interestingly, the perceptual responses that take place in the visual cortex are activated not only by motion itself, but by occlusions, dis-occlusions, motion composition, and moving edges. Furthermore, psychological vision have linked the brain's ability to understand motion composition from visual information to high level scene understanding like object segmentation and recognition
Brulin, Mathieu. "Analyse sémantique d'un trafic routier dans un contexte de vidéo-surveillance." Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14589/document.
Full textAutomatic traffic monitoring plays an important role in traffic surveillance. Video cameras are relatively inexpensive surveillance tools, but necessitate robust, efficient and automated video analysis algorithms. The loss of information caused by the formation of images under perspective projection made the automatic task of detection and tracking vehicles a very challenging problem, but essential to extract a semantic interpretation of vehicles behaviors. The work proposed in this thesis comes from a collaboration between the LaBRI (Laboratoire Bordelais de Recherche en Informatique) and the company Adacis. The aim is to elaborate a complete video-surveillance system designed for automatic incident detection.To reach this objective, traffic scene analysis proceeds from low-level processing to high-level descriptions of the traffic, which can be in a wide variety of type: vehicles entering or exiting the scene, vehicles collisions, vehicles' speed that are too fast or too low, stopped vehicles or objects obstructing part of the road... A large number of road traffic monitoring systems are based on background subtraction techniques to segment the regions of interest of the image. Resulted regions are then tracked and trajectories are used to extract a semantic interpretation of the vehicles behaviors.The motion detection is based on a statistical model of background color. The model used is a mixture model of probabilistic laws, which allows to characterize multimodal distributions for each pixel. Estimation of optical flow, a gradient difference estimation and shadow and highlight detection are used to confirm or invalidate the segmentation results.The tracking process is based on a predictive filter using a motion model with constant velocity. A simple Kalman filter is employed, which allow to predict state of objets based on a \textit{a priori} information from the motion model.The behavior analysis step contains two approaches : the first one consists in exploiting information from low-level and mid-level analysis. Objects and their trajectories are analysed and used to extract abnormal behavior. The second approach consists in analysing a spatio-temporal slice in the 3D video volume. The extracted maps are used to estimate statistics about traffic and are used to detect abnormal behavior such as stopped vehicules or wrong way drivers.In order to help the segmentaion and the tracking processes, a structure model of the scene is proposed. This model is constructed using an unsupervised learning step. During this learning step, gradient information from the background image and typical trajectories of vehicles are estimated. The results are combined to estimate the vanishing point of the scene, the lanes boundaries and a rough depth estimation is performed. In parallel, a statistical model of the trafic flow direction is proposed. To deal with periodic data, a von-Mises mixture model is used to characterize the traffic flow direction
Toumoulin, Christine. "Extraction de formes, Suivi d'objets déformables et Reconstruction en Imagerie Médicale : Application à l'Angiographie R-X et au scanner X multibarette." Habilitation à diriger des recherches, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00966605.
Full textGiraldo, Zuluaga Jhony Heriberto. "Graph-based Algorithms in Computer Vision, Machine Learning, and Signal Processing." Electronic Thesis or Diss., La Rochelle, 2022. http://www.theses.fr/2022LAROS037.
Full textGraph representation learning and its applications have gained significant attention in recent years. Notably, Graph Neural Networks (GNNs) and Graph Signal Processing (GSP) have been extensively studied. GNNs extend the concepts of convolutional neural networks to non-Euclidean data modeled as graphs. Similarly, GSP extends the concepts of classical digital signal processing to signals supported on graphs. GNNs and GSP have numerous applications such as semi-supervised learning, point cloud semantic segmentation, prediction of individual relations in social networks, modeling proteins for drug discovery, image, and video processing. In this thesis, we propose novel approaches in video and image processing, GNNs, and recovery of time-varying graph signals. Our main motivation is to use the geometrical information that we can capture from the data to avoid data hungry methods, i.e., learning with minimal supervision. All our contributions rely heavily on the developments of GSP and spectral graph theory. In particular, the sampling and reconstruction theory of graph signals play a central role in this thesis. The main contributions of this thesis are summarized as follows: 1) we propose new algorithms for moving object segmentation using concepts of GSP and GNNs, 2) we propose a new algorithm for weakly-supervised semantic segmentation using hypergraph neural networks, 3) we propose and analyze GNNs using concepts from GSP and spectral graph theory, and 4) we introduce a novel algorithm based on the extension of a Sobolev smoothness function for the reconstruction of time-varying graph signals from discrete samples
Legrand, Capucine. "Exploitation conjointe de l'information spatiale et temporelle d'une séquence stéréoscopique d'images synchronisées : application à la détection d'obstacles dans une scène routière." Compiègne, 2009. http://www.theses.fr/2009COMP1794.
Full textMy research focuses on trajectory planning and control of autonomous vehicles. This work is a part of an extremely ambitions project launched by the Heudiasyc laboratory about autonomous driving at high speed (longitudinal speed greater to 5m/s : 18km/h). With regard to the control of autonomous vehicles at high speed, a lateral controller using higher-order sliding mode control is proposed. Given the implicit similarity between the sliding mode and the principle of immersion and invariance, two controllers using the principle of immersion and invariance have been subsequently proposed in order to improve the performance with respect to the sliding mode. The development of these new controllers shows very strong robust stability which leads us to study the intrinsic properties of the system. A study of the passivity properties of the system is also carried out, showing some interesting characteristics of the system. Hence, a robust Passivity-based controller has been developed. Regarding the navigation, we have developed two navigation algorithms based on the tentacles method. Subsequently, a feasibility study of trajectory generation strategies for high speed driving is conducted. The outcorne of the simulation proved that the algorithms gave out good results with respect to the expected objectives of obstacle avoidance and global reference path following. Control and motion planning algorithms developed were validated offline by simulation with real data. They have been also tested on a realistic simulator
Kumar, Ratnesh. "Segmentation vidéo et suivi d'objets multiples." Thesis, Nice, 2014. http://www.theses.fr/2014NICE4135/document.
Full textIn this thesis we propose novel algorithms for video analysis. The first contribution of this thesis is in the domain of video segmentation wherein the objective is to obtain a dense and coherent spatio-temporal segmentation. We propose joining both spatial and temporal aspects of a video into a single notion Fiber. A fiber is a set of trajectories which are spatially connected by a mesh. Fibers are built by jointly assessing spatial and temporal aspects of the video. Compared to the state-of-the-art, a fiber based video segmentation presents advantages such as a natural spatio-temporal neighborhood accessor by a mesh, and temporal correspondences for most pixels in the video. Furthermore, this fiber-based segmentation is of quasi-linear complexity w.r.t. the number of pixels. The second contribution is in the realm of multiple object tracking. We proposed a tracking approach which utilizes cues from point tracks, kinematics of moving objects and global appearance of detections. Unification of all these cues is performed on a Conditional Random Field. Subsequently this model is optimized by a combination of message passing and an Iterated Conditional Modes (ICM) variant to infer object-trajectories. A third, minor, contribution relates to the development of suitable feature descriptor for appearance matching of persons. All of our proposed approaches achieve competitive and better results (both qualitatively and quantitatively) than state-of-the-art on open source datasets
Massich, Joan. "Segmentation d'objets déformables en imagerie ultrasonore." Thesis, Dijon, 2013. http://www.theses.fr/2013DIJOS090/document.
Full textBreast cancer is the second most common type of cancer being the leading cause of cancer death among females both in western and in economically developing countries. Medical imaging is key for early detection, diagnosis and treatment follow-up. Despite Digital Mammography (DM) remains the reference imaging modality, Ultra-Sound (US) imaging has proven to be a successful adjunct image modality for breast cancer screening, specially as a consequence of the discriminative capabilities that US offers for differentiating between solid lesions that are benign or malignant. Despite US usability,US suffers inconveniences due to its natural noise that compromises the diagnosis capabilities of radiologists. Therefore the research interest in providing radiologists with Computer Aided Diagnosis (CAD) tools to assist the doctors during decision taking. This thesis analyzes the current strategies to segment breast lesions in US data in order to infer meaningful information to be feet to CAD, and proposes a fully automatic methodology for generating accurate segmentations of breast lesions in US data with low false positive rates
Habibi, Arash. "Visualisation d'objets très déformables : relations mouvement-forme-image." Grenoble INPG, 1997. http://www.theses.fr/1997INPG0008.
Full textThis work falls within the field of image synthesis and computer animation by physical modelling. The modelling and visualization of physical objets consists in a work on shape, motion and image. The more a given reference object is deformable and the more the relation between these three phenomena may grow complex. We study this relation and determine in which conditions the behaviour (shape, motion and image) of an object may be represented by several models which are autonomous (multi-scale modelling) and discoupled (clothing « habillage »). In particular, we study highly deformable objects. A shape modeler for this type of object must verify a certain number of properties. We present a shape model verifying these conditions. We study its dynamic behaviour and present the resulting images
Books on the topic "Segmentation d'objets en mouvement"
Computational analysis of visual motion. New York: Plenum Press, 1994.
Find full textJähne, Bernd. Digital image processing: Concepts, algorithms, and scientific applications. Berlin: Springer-Verlag, 1991.
Find full textDigital image processing. 6th ed. Berlin: Springer, 2005.
Find full textJähne, Bernd. Digital image processing: Concepts, algorithms, and scientific applications. 2nd ed. Berlin: Springer-Verlag, 1993.
Find full textDigital image processing: Concepts, algorithms, and scientific applications. 4th ed. Berlin: Springer, 1997.
Find full textJähne, Bernd. Digital image processing: Concepts, algorithms, and scientific applications. 3rd ed. Berlin: Springer-Verlag, 1995.
Find full textMitiche, Amar. Computational Analysis of Visual Motion. Springer, 2013.
Find full text