Search results for "Computer vision"

showing 10 items of 2353 documents

Mélange de Gaussiennes Photométriques pour l'Asservissement Visuel Virtuel Direct d'une Caméra Omnidirectionnelle

2021

International audience; Cet article traite du suivi de pose direct basé modèle 3D. Nous considérons la transformation d’images omnidirectionnelles en Mélange de Gaussiennes Photométriquesn (MGP) comme primitives directes. Les contributions sont d’adapter l’optimisation de pose aux caméras omnidirectionnelles et de repenser les règles d’initialisation et d’optimisation du paramètre d’extension du MGP. Plusieurs évaluations montrent que cette approche augmente la taille du domaine de convergence. L’application à des images acquises avec un robot mobile placé dans un environnement urbain, représenté par un grand nuage de points 3D coloré, montre une robustesse significative aux grands mouvemen…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Asservissement visuelSuivi.Vision Omnidirectionnelle[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO]Computer Science [cs][INFO] Computer Science [cs]
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ROBUST ROAD SIGNS SEGMENTATION IN COLOR IMAGES

2012

International audience; This paper presents an efficient method for road signs segmentation in color images. Color segmentation of road signs is a difficult task due to variations in the image acquisition conditions. Therefore, a color constancy algorithm is usually applied prior to segmentation, which increases the computation time. The proposed method is based on a log-chromaticity color space which shows good invariance properties to changing illumination. Thus, the method is simple and fast since it does not require color constancy algorithms. Experiments with a large dataset and comparison with other approaches, show the robustness and accuracy of the method in detecting road signs in …

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Color segmentationRoad sign detectionLog-chromaticity color space.ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Log-chromaticity color space[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Color constancy
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Background subtraction with multispectral video sequences

2014

International audience; Motion analysis of moving targets is an important issue in several applications such as video surveillance or robotics. Background subtraction is one of the simplest and widely used techniques for moving target detection in video sequences. In this paper, we investigate the advantages of using a multispectral video acquisition system of more than three bands for background subtraction over the use of trichromatic or monochromatic video sequences. To this end, we have established a dataset of multispectral videos with a manual annotation of moving objects. To the best of our knowledge, this is the first publicly available dataset of multispectral video sequences. Expe…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]ComputingMethodologies_PATTERNRECOGNITIONComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Apprentissage incrémental pour la détection de chute de personnes âgées

2015

International audience; Dans ce papier, nous proposons une méthodologie d'évolution supervisée d'un modèle de classification, spécifique à un système de détection de chute de personnes mis au point précédemment. Cette méthodologie met en oeuvre la méthode de détection, un protocole d'apprentissage incrémental ou évolutif, et une méthode d'évaluation et de comparaison des performances, devant conduire à une amélioration des capacités de détection de chutes sur un système embarqué de type caméra intelligente.

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Détection de Chute[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]apprentissage incrémental.temps réel[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Road Signs Detection and Reconstruction using Gielis Curves

2012

International audience; Road signs are among the most important navigation tools in transportation systems. The identification of road signs in images is usually based on first detecting road signs location using color and shape information. In this paper, we introduce such a two-stage detection method. Road signs are located in images based on color segmentation, and their corresponding shape is retrieved using a unified shape representation based on Gielis curves. The contribution of our approach is the shape reconstruction method which permits to detect any common road sign shape, i.e. circle, triangle, rectangle and octagon, by a single algorithm without any training phase. Experimental…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Gielis curves.Color segmentationRoad sign detectionGielis curves[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Contour fitting
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An SVD-Based Approach for Ghost Detection and Removal in High Dynamic Range Images

2012

International audience; In this paper, we propose a simple method for the ghost detection problem in the context of merging multiple low dynamic range (LDR) images to form a high dynamic range (HDR) image. We show that the second biggest singular values extracted over local spatio-temporal neighbourhoods can be effectively used for ghost region detection. Furthermore, we combine the proposed method with an exposure fusion technique to generate final HDR image free of ghosting artefacts. We present experimental results to illustrate the efficiency of the proposed method and quantitative comparison with other existing approaches show the good performance of our method in detecting and removin…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]HDR ImagesGhost detectionHigh Energy Physics::LatticeComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]SVDGeneralLiterature_MISCELLANEOUS
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Trois algorithmes intelligents pour la numérisation 3D automatique d'objets inconnus

2013

National audience; Ce papier propose trois approches itératives et intelligentes de planification de vue pour la numérisation 3D d'objets sans connaissance a priori de leurs formes. La première méthode est une approche simple et naïve basée sur la génération d'un ensemble de points de vues par échantillonnage régulier de l'enveloppe englobante des données acquises. La deuxième méthode est basée sur une analyse de l'orientation des différentes parties acquises. La troisième méthode vise à explorer les parties de l'objet qui figurent dans la limite du champ de visibilité et est basée sur un couplage de la visibilité angulaire avec la visibilité réelle par lancer de rayons. Les résultats de nu…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Méthode Non-Basée sur un modèle[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Numérisation 3D[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Planification de prise de vuesAutoma- tisationMéthode Non-Basée sur un modèle.
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Tracking in Presence of Total Occlusion and Size Variation using Mean Shift and Kalman Filter

2011

International audience; The classical mean shift algorithm for tracking in perfectly arranged conditions constitutes a good object tracking method. However, in the real environment it presents some limitations, especially under the presence of noise, objects with varying size, or occlusions. In order to deal with these problems, this paper proposes a reliable object tracking algorithm using mean shift and the Kalman filter, which was added to the traditional algorithm as a predictor when no reliable model of the object being tracked is found. Experimental work demonstrates that the proposed mean shift Kalman filter algorithm improves the tracking performance of the classical algorithms in c…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]OcclusionSize VariationTrackingVision par ordinateur et reconnaissance de formes [Informatique][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Kalman FilterMean Shift Filter
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Estimation de la pose d'une caméra dans un environnement connu à partir d'un recalage 2D-3D

2014

National audience; Nous proposons une méthode directe de recalage robuste 2D-3D permettant de localiser une caméra dans un environnement 3D connu. Il s'agit d'un problème rendu particulièrement difficile par l'absence de correspondances entre les points 3D du nuage et les points 2D. A cette difficulté, s'ajoute la différence d'échelle entre le nuage 3D connu et le nuage 3D reconstruit à partir d'images qui, de plus, peut contenir des points aberrants et des occultations. Notre méthode consiste en l'optimisation d'une fonctionnelle de manière itérative en deux étapes : estimation de la pose de la caméra et mise en correspondance 2D-3D. Ainsi, nous obtenons une méthode d'estimation conjointe …

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]SfM[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]reconstruction 3DEstimation de pose[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Learning Bag of Spatio-Temporal Features for Human Interaction Recognition

2019

Bag of Visual Words Model (BoVW) has achieved impressive performance on human activity recognition. However, it is extremely difficult to capture high-level semantic meanings behind video features with this method as the spatiotemporal distribution of visual words is ignored, preventing localization of the interactions within a video. In this paper, we propose a supervised learning framework that automatically recognizes high-level human interaction based on a bag of spatiotemporal visual features. At first, a representative baseline keyframe that captures the major body parts of the interacting persons is selected and the bounding boxes containing persons are extracted to parse the poses o…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Sum of HistogramsBag of Visual WordsHuman interaction[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingSVMEdge-based regionMSER3D-SIFT
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