Advances in description of 3D human motion

International audienceThis paper aims to provide a comprehensive reference source on depth-based human motion descriptors. Motion description is a challenging problem which became popular with recent advances in 3D computer vision. Our purpose is twofold. First, we introduce the main trends in human 3D motion descriptor design and evaluation. Second, we present a review of recent methods belonging to three different application categories: action recognition, gesture recognition and gait assessment. Selected categories have different specifics, which allow us to highlight aspects of a motion descriptor construction. A comparison of different methods by their main characteristics is provided. Finally, possible directions and recommendations for future research in 3D motion description are outlined

CARI'96 : actes du 3ème colloque africain sur la recherche en informatique = CARI'96 : proceedings of the 3rd African conference on research in computer science

The goal of this study is to estimate the motion between two successive images in a sequence. In this paper, we present an approach of the regularization problem which enables us to take into account motion discontinuities. This approach is based on the theory of Markov random fields and the Fourier analysis. (Résumé d'auteur

The shifting discourse of the European Central Bank: Exploring structural space in semantic networks

Convenient access to vast and untapped collections of documents generated by organizations is a valuable resource for research. These documents (e.g., Press releases, reports, speech transcriptions, etc.) are a window into organizational strategies, communication patterns, and organizational behavior. However, the analysis of such large document corpora does not come without challenges. Two of these challenges are 1) the need for appropriate automated methods for text mining and analysis and 2) the redundant and predictable nature of the formalized discourse contained in these collections of texts. Our article proposes an approach that performs well in overcoming these particular challenges for the analysis of documents related to the recent financial crisis. Using semantic network analysis and a combination of structural measures, we provide an approach that proves valuable for a more comprehensive analysis of large and complex semantic networks of formal discourse, such as the one of the European Central Bank (ECB). We find that identifying structural roles in the semantic network using centrality measures jointly reveals important discursive shifts in the goals of the ECB which would not be discovered under traditional text analysis approaches

Signal processing for image enhancement and multimedia processing

Traditionally, signal processing techniques lay at the foundation of multimedia data processing and analysis. In the past few years, a new wave of advanced signal-processing techniques has delivered exciting results, increasing system's capabilities of efficiently exchanging image data and extracting useful knowledge. Signal Processing for Image Enhancement and Multimedia Processing is written by global experts who have extended the best papers presented at the SITIS 2006 International Conference to chapter versions. This edited book presents research results on the application of advanced signal processing techniques for improving the value of image and video data. In addition, this volume includes discussions on feature-based techniques for deep, feature-oriented analysis of images, plus new results on video coding on the time-honored topic of securing image information. Signal Processing for Image Enhancement and Multimedia Processing is designed for a professional audience of practitioners and researchers in industry. It is also suitable as a reference or secondary text for advanced-level students in computer science and engineering

Comparative evaluation of methods for filtering Kinect depth data

The release of the Kinect has fostered the design of novel methods and techniques in several application domains. It has been tested in different contexts, which span from home entertainment to surgical environments. Nonetheless, to promote its adoption to solve real-world problems, the Kinect should be evaluated in terms of precision and accuracy. Up to now, some filtering approaches have been proposed to enhance the precision and accuracy of the Kinect sensor, and preliminary studies have shown promising results. In this work, we discuss the results of a study in which we have compared the most commonly used filtering approaches for Kinect depth data, in both static and dynamic contexts, by using novel metrics. The experimental results show that each approach can be profitably used to enhance the precision and/or accuracy of Kinect depth data in a specific context, whereas the temporal filtering approach is able to reduce noise in different experimental conditions

Caractérisation des discontinuités-images par l\'approche de vecteur de texture: application à des images RSO d\'ERS 2

L\'objectif de ce travail est le traitement d\'images radar à synthèse d\'ouverture (RSO) d\'ERS pour l\'identification et l\'extraction des discontinuités-images en s\'appuyant sur le concept de vecteur de texture dans une classification supervisée. Les paramètres de texture retenus sont reformulés aux ordres n>2, à partir de leurs différentes formulations mathématiques classiques à l\'ordre 2, basées sur les matrices de co-occurrences des niveaux de gris. La particularité de cette approche réside dans le fait que chaque pixel est entièrement caractérisé par son vecteur de texture. En effet, le vecteur de texture renseigne mieux sur le pixel, car il tient compte du voisinage du pixel considéré. Cette méthode est appliquée à deux images RSO : la première dans la région semi-montagneuse de Man (à l\'Ouest de la Côte d\'Ivoire) et la seconde dans la zone littorale Camerounaise. Le tronçon hydrographique du Sassandra (principal fleuve de l\'Ouest de la Côte d\'Ivoire) et des linéaments morphostructuraux ont été extraits sur la première image et le trait de côte du littoral Camerounais a été extrait sur la seconde. The main objective of this work is the processing of ERS SAR images for identification and extraction of image-discontinuities, using the concept of texture vector in a supervised classification. Using the classical formulation of order 2 texture parameters and based on the Neighboring Gray-Level Dependence Matrix, the formulation of these parameters has been extended to orders n>2. The originality of this method lies in the fact that each image pixel is fully characterized by its texture vector. This texture vector gives more information about the pixel since it is based on the neighbourhood. This methodology has been applied on two ERS SAR images, the first in the semi-mountainous region of Man in Côte d\'Ivoire, and the second in the Cameroonian littoral region. The Sassandra River (the main river of western Côte d\'Ivoire) and others morphostructural lineaments are extracted from the first image and the Cameroonian littoral coast is extracted from the second image. Keywords: Image RSO, vecteur de texture, classification, Cameroun, Côte d\'Ivoire.SAR image, texture vector, classification, Cameroon, Côte d\'Ivoire. Journal des Sciences Pour l\'Ingénieur. Vol. 7 2006: pp. 20-2

Object 3D reconstruction based on photometric stereo and inverted rendering

Methods for 3D reconstruction such as Photometric stereo recover the shape and reflectance properties using multiple images of an object taken with variable lighting conditions from a fixed viewpoint. Photometric stereo assumes that a scene is illuminated only directly by the illumination source. As result, indirect illumination effects due to inter-reflections introduce strong biases in the recovered shape. Our suggested approach is to recover scene properties in the presence of indirect illumination. To this end, we proposed an iterative PS method combined with a reverted Monte-Carlo ray tracing algorithm to overcome the inter-reflection effects aiming to separate the direct and indirect lighting. This approach iteratively reconstructs a surface considering both the environment around the object and its concavities. We demonstrate and evaluate our approach using three datasets and the overall results illustrate improvement over the classic PS approaches.Comment: 8 pages, 11 figure, SITIS conferenc