Object Recognition and Pose Estimation across Illumination Changes

In this paper, we present a new algorithm for color-based object recognition that detects objects and estimates their pose (position and orientation) in cluttered scenes observed under uncontrolled illumination conditions. As with so many other color-based object-recognition algorithms, color histograms are also fundamental to our approach; however, we use histograms obtained from overlapping subwindows, rather than the entire image. Furthermore, each local histogram is normalized using greyworld normalization in order to be as less sensitive to illumination as possible. An object from a database of prototype objects is identified and located in an input image by matching the subwindow contents. The prototype is detected in the input whenever many good histogram matches are found between the subwindows of the input image and those of the prototype. In essence, normalized color histograms of subwindows are the local features being matched. Once an object has been recognized, its 2D pose is found by approximating the geometrical transformation most consistently mapping the locations of prototype’s subwindows to their matched subwindow locations in the input image

Object recognition by intersection between adapted color histograms

Most of object recognition schemes fail in case of illumination changes between the color image acquisitions. One of the most widely used solutions to cope with this problem is to compare the images by means of the intersection between invariant color histograms. Unlike the classical invariant color histograms approach which independently analyzes each image, we consider each pair constituted by the query image and one of the target images constructed during the retrieval. In this paper, we propose a new approach based on color histograms which are adapted to each pair constituted by the query image and one of the target images. These adapted color histograms are determined so that their intersection is high only when the objects contained in the two images are similar. The adapted color histograms processing is based on an original model of illumination changes based on the rank measures of the pixels within the color component images.Dans cet article, nous abordons le problème de la reconnaissance des objets sous éclairage non contrôlé par la recherche de toutes les images d'une base qui contiennent le même objet que celui représenté dans une image requête. Nous nous intéressons aux problèmes soulevés par les modifications des images couleur consécutives à des changements d'illuminant. Les images considérées dans cet article contiennent un seul objet placé sur un fond uniforme et éclairé avec un illuminant qui diffère d'une image à l'autre. Les méthodes classiques basées sur des histogrammes invariants ne fournissent pas des résultats satisfaisants en termes de reconnaissance d'objets éclairés par différents illuminants. Nous proposons de traiter ce problème, non pas en analysant les images de la base indépendamment les unes des autres, mais en analysant tous les couples constitués de l'image requête et de chacune des images candidates. Plus précisément, nous proposons d'analyser chaque couple d'histogrammes couleur pour comparer le contenu de chaque couple d'images. Pour cela, la procédure détermine un couple d'histogrammes couleur dits « spécifiques » à chaque couple d'histogrammes couleur considéré, de telle sorte que l'intersection entre ces histogrammes couleur spécifiques soit élevée uniquement lorsque les deux objets contenus dans les deux images sont similaires. Cette procédure est basée sur une nouvelle hypothèse sur les conséquences d'un changement d'illuminant qui ne porte pas directement sur les couleurs des pixels, mais sur les mesures de rang des pixels

Statut de la Sterne naine, Sterna albifrons, en France : recolonisation des anciens sites de reproduction ?

Muselet D. Statut de la Sterne naine, Sterna albifrons, en France : recolonisation des anciens sites de reproduction ?. In: Revue d'Écologie. Supplément n°4, 1987. pp. 280-281

Color person image indexing and retrieval

International audienc

Color person image indexing and retrieval

International audienc

Cooccurrence matrices of color feature vectors for multi-camera vehicle identification

International audienc

Physical modelling of vehicle performance in high-amplitude and high-rate manoeuvres

The disciplines of hydrodynamics and aerodynamics use similar theory and methods in experimental work on high-amplitude and high-rate manoeuvres with free-flight and free-swimming models, in analysis techniques when extracting dynamic stability derivatives from measured free trajectories and measured hydrodynamic or aerodynamic loads, and in the design of suitable control systems for such manoeuvres in up to six degrees-offreedom. Research using the NRC-IMD Marine Dynamic Test Facility (MDTF) has established new methods and standards in each of these areas. This paper outlines the relevant capabilities of MDTF and discusses some recent analyses of data from submarine model experiments.NRC publication: Ye

The NRC-IMD Marine Dynamics Test Facility: A Six-Degree-of-Freedom Forced-Motion Apparatus for Underwater Vehicle Testing

The Marine Dynamic Test Facility (MDTF) is a new experimental apparatus that is optimized for dynamically testing large underwater vehicle models well into the nonlinear regime. Its effective use requires careful experimental design and advanced methods of data analysis. This paper describes the MDTF and discusses a number of the issues for underwater vehicle testing that have been encountered during the first year since its commissioning.NRC publication: Ye

A physical map of 30,000 human genes

A map of 30,181 human gene-based markers was assembled and integrated with the current genetic map by radiation hybrid mapping. The new gene map contains nearly twice as many genes as the previous release, includes most genes that encode proteins of known function, and is twofold to threefold more accurate than the previous version. A redesigned, more informative and functional World Wide Web site (www.ncbi.nlm.nih.gov/genemap) provides the mapping information and associated data and annotations. This resource constitutes an important infrastructure and tool for the study of complex genetic traits, the positional cloning of disease genes, the cross-referencing of mammalian genomes, and validated human transcribed sequences for large-scale studies of gene expression