Face Class Modeling based on Local Appearance for Recognition

International audienceThis work proposes a new formulation of the objects modeling combining geometry and appearance. The object local appearance location is referenced with respect to an invariant which is a geometric landmark. The appearance (shape and texture) is a combination of Harris-Laplace descriptor and local binary pattern (LBP), all is described by the invariant local appearance model (ILAM). We applied the model to describe and learn facial appearances and to recognize them. Given the extracted visual traits from a test image, ILAM model is performed to predict the most similar features to the facial appearance, first, by estimating the highest facial probability, then in terms of LBP Histogram-based measure. Finally, by a geometric computing the invariant allows to locate appearance in the image. We evaluate the model by testing it on different images databases. The experiments show that the model results in high accuracy of detection and provides an acceptable tolerance to the appearance variability

A fast voxelization algorithm for trilinearly interpolated isosurfaces

International audienceIn this work we propose a new method for a fast incremental voxelization of isosurfaces obtained by the trilinear interpolation of 3D data. Our objective consists in the fast generation of subvoxelized iso-surfaces extracted by a point-based technique similar to the Dividing Cubes algorithm. Our technique involves neither an exhaustive scan search process nor a graph-based search approach when generating iso-surface points. Instead an optimized incremental approach is adopted here for a rapid isosurface extraction. With a sufficient sampling subdivision criteria around critical points, the extracted isosurface is both correct and topologically consistent with respect to the piece-wise trilinear interpolant. Furthermore, the discretiza-tion scheme used in our method ensures obtaining thin-one voxel width-isosurfaces as compared to the given by the Dividing Cubes algorithm. The resultant sub-voxelized isosurfaces are efficiently tested against all possible configurations of the trilinear interpolant and real-world datasets

EYE AND GAZE TRACKING ALGORITHM FOR COLLABORATIVE LEARNING SYSTEM

International audienceOur work focuses on the interdisciplinary field of detailed analysis of behaviors exhibited by individuals during sessions of distributed collaboration. With a particular focus on ergonomics, we propose new mechanisms to be integrated into existing tools to enable increased productivity in distributed learning and working. Our technique is to record ocular movements (eye tracking) to analyze various scenarios of distributed collaboration in the context of computer-based training. In this article, we present a low-cost oculometric device that is capable of making ocular measurements without interfering with the natural behavior of the subject. We expect that this device could be employed anywhere that a natural, non-intrusive method of observation is required, and its low-cost permits it to be readily integrated into existing popular tools, particularly E-learning campus

A Parametric Algorithm for Skyline Extraction

International audienceThis paper is dedicated to the problem of automatic skyline extraction in digital images. The study is motivated by the needs, expressed by urbanists, to describe in terms of geometrical features, the global shape created by man-made buildings in urban areas. Skyline extraction has been widely studied for navigation of Unmanned Aerial Vehicles (drones) or for geolocalization, both in natural and urban contexts. In most of these studies, the skyline is defined by the limit between sky and ground objects, and can thus be resumed to the sky segmentation problem in images. In our context, we need a more generic definition of skyline, which makes its extraction more complex and even variable. The skyline can be extracted for different depths, depending on the interest of the user (far horizon, intermediate buildings, near constructions , ...), and thus requires a human interaction. The main steps of our method are as follows: we use a Canny filter to extract edges and allow the user to interact with filter's parameters. With a high sensitivity , all the edges will be detected, whereas with lower values, only most contrasted contours will be kept by the filter. From the obtained edge map, an upper envelope is extracted, which is a disconnected approximation of the skyline. A graph is then constructed and a shortest path algorithm is used to link discontinuities. Our approach has been tested on several public domain urban and natural databases, and have proven to give better results that previously published methods

Shape: automatic conformation prediction of carbohydrates using a genetic algorithm

<p>Abstract</p> <p>Background</p> <p>Detailed experimental three dimensional structures of carbohydrates are often difficult to acquire. Molecular modelling and computational conformation prediction are therefore commonly used tools for three dimensional structure studies. Modelling procedures generally require significant training and computing resources, which is often impractical for most experimental chemists and biologists. <monospace>Shape</monospace> has been developed to improve the availability of modelling in this field.</p> <p>Results</p> <p>The <monospace>Shape</monospace> software package has been developed for simplicity of use and conformation prediction performance. A trivial user interface coupled to an efficient genetic algorithm conformation search makes it a powerful tool for automated modelling. Carbohydrates up to a few hundred atoms in size can be investigated on common computer hardware. It has been shown to perform well for the prediction of over four hundred bioactive oligosaccharides, as well as compare favourably with previously published studies on carbohydrate conformation prediction.</p> <p>Conclusion</p> <p>The <monospace>Shape</monospace> fully automated conformation prediction can be used by scientists who lack significant modelling training, and performs well on computing hardware such as laptops and desktops. It can also be deployed on computer clusters for increased capacity. The prediction accuracy under the default settings is good, as it agrees well with experimental data and previously published conformation prediction studies. This software is available both as open source and under commercial licenses.</p

Programmation dynamique et traitement d'images sur machines parallèles à mémoire distribuée

Nous étudions la mise en œuvre d'algorithmes parallèles sur des ordinateurs a mémoire distribuée. A travers plusieurs exemples issus de la programmation dynamique, de l'algèbre linéaire et du traitement d'images, nous exposons les problèmes lies a la programmation de ces machines: topologie d'interconnexion, stratégie d'allocation des données, équilibrage des calculs et minimisation du volume de communication inter-processeurs. Les exemples étudiés sont pour la plupart des algorithmes séquentiels couteux en temps de calcul et en place mémoire, et pour lesquels il est très intéressant d'avoir une parallélisation efficace. Nous avons choisi des problèmes dont l'implémentation sur des machines a mémoire distribuée n'est pas aisée, essentiellement a cause de la grande interdépendance entre les différentes taches composant les algorithme

Face Class Modeling based on Local Appearance for Recognition

International audienceThis work proposes a new formulation of the objects modeling combining geometry and appearance. The object local appearance location is referenced with respect to an invariant which is a geometric landmark. The appearance (shape and texture) is a combination of Harris-Laplace descriptor and local binary pattern (LBP), all is described by the invariant local appearance model (ILAM). We applied the model to describe and learn facial appearances and to recognize them. Given the extracted visual traits from a test image, ILAM model is performed to predict the most similar features to the facial appearance, first, by estimating the highest facial probability, then in terms of LBP Histogram-based measure. Finally, by a geometric computing the invariant allows to locate appearance in the image. We evaluate the model by testing it on different images databases. The experiments show that the model results in high accuracy of detection and provides an acceptable tolerance to the appearance variability

Détection des événements rares dans des vidéos

Le travail présenté dans cette étude se place dans le contexte de l analyse automatique des vidéos. A cause du nombre croissant des données vidéo, il est souvent difficile, voire impossible qu un ou plusieurs opérateurs puissent les regarder toutes. Une demande récurrente est d identifier les moments dans la vidéo quand il y a quelque chose d inhabituel qui se passe, c est-à-dire la détection des événements anormaux.Nous proposons donc plusieurs algorithmes permettant d identifier des événements inhabituels, en faisant l hypothèse que ces événements ont une faible probabilité. Nous abordons plusieurs types d événements, de l analyse des zones en mouvement à l analyse des trajectoires des objets suivis.Après avoir dédié une partie de la thèse à la construction d un système de suivi,nous proposons plusieurs mesures de similarité entre des trajectoires. Ces mesures, basées sur DTW (Dynamic Time Warping), estiment la similarité des trajectoires prenant en compte différents aspects : spatial, mais aussi temporel, pour pouvoir - par exemple - faire la différence entre des trajectoires qui ne sont pas parcourues de la même façon (en termes de vitesse de déplacement). Ensuite, nous construisons des modèles de trajectoires, permettant de représenter les comportements habituels des objets pour pouvoir ensuite détecter ceux qui s éloignent de la normale.Pour pallier les défauts de suivi qui apparaissent dans la pratique, nous analysons les vecteurs de flot optique et nous construisons une carte de mouvement. Cette carte modélise sous la forme d un codebook les directions privilégiées qui apparaissent pour chaque pixel, permettant ainsi d identifier tout déplacement anormal, sans avoir pour autant la notion d objet suivi. En utilisant la cohérence temporelle, nous pouvons améliorer encore plus le taux de détection, affecté par les erreurs d estimation de flot optique. Dans un deuxième temps, nous changeons la méthode de constructions de cette carte de mouvements, pour pouvoir extraire des caractéristiques de plus haut niveau l équivalent des trajectoires, mais toujours sans nécessiter le suivi des objets. Nous pouvons ainsi réutiliser partiellement l analyse des trajectoires pour détecter des événements rares.Tous les aspects présentés dans cette thèse ont été implémentés et nous avons construit certaines applications, comme la prédiction des déplacements des objets ou la mémorisation et la recherche des objets suivis.The growing number of video data makes often difficult, even impossible, any attemptof watching them entirely. In the context of automatic analysis of videos, a recurring request is to identify moments in the video when something unusual happens.We propose several algorithms to identify unusual events, making the hypothesis that these events have a low probability. We address several types of events, from those generates by moving areas to the trajectories of objects tracked. In the first part of the study, we build a simple tracking system. We propose several measures of similarity between trajectories. These measures give an estimate of the similarity of trajectories by taking into account both spatial and/or temporal aspects. It is possible to differentiate between objects moving on the same path, but with different speeds. Based on these measures, we build models of trajectories representing the common behavior of objects, so that we can identify those that are abnormal.We noticed that the tracking yields bad results, especially in crowd situations. Therefore, we use the optical flow vectors to build a movement model based on a codebook. This model stores the preferred movement directions for each pixel. It is possible to identify abnormal movement at pixel-level, without having to use a tracker. By using temporal coherence, we can further improve the detection rate, affected by errors of estimation of optic flow. In a second step, we change the method of construction of this model. With the new approach, we can extract higher-level features the equivalent trajectories, but still without the notion of object tracking. In this situation, we can reuse partial trajectory analysis to detect rare events.All aspects presented in this study have been implemented. In addition, we have design some applications, like predicting the trajectories of visible objects or storing and retrieving tracked objects in a database.LYON2/BRON-BU (690292101) / SudocSudocFranceF

Elastic load balancing for image processing algorithms

International audienceno abstrac