Cooperative Fusion for Multi-Obstacles Detection With Use of Stereovision and Laser Scanner

We propose a new cooperative fusion approach between stereovision and laser scanner in order to take advantage of the best features and cope with the drawbacks of these two sensors to perform robust, accurate and real time-detection of multi-obstacles in the automotive context. The proposed system is able to estimate the position and the height, width and depth of generic obstacles at video frame rate (25 frames per second). The vehicle pitch, estimated by stereovision, is used to filter laser scanner raw data. Objects out of the road are removed using road lane information computed by stereovision. Various fusion schemes are proposed and one is experimented. Results of experiments in real driving situations (multi-pedestrians and multi-vehicles detection) are presented and stress the benefits of our approach.Raphaël Labayrade was born in France, in 1976. He received the M.S. degree in 2000 from the university of Saint Etienne, and he was also graduate from the ENTPE engineer school in 2000. In 2004 he received the Ph.D. degree from the university Pierre et Marie Curie Paris VI. In his thesis he proposed a new approach for detecting road obstacles using stereovision in a generic, fast and robust manner.He is currently a researcher at INRETS since 2004 in the perception team of the LIVIC department and works on automated highway and on on-board driving assistance systems. His main work deals with obstacles detection using data fusion but he is also interested in road lane recognition. He is involved for vision tasks in various european and french projects dealing with intelligent vehicles (Carsense, Micado, Arcos). He teaches at Jussieu (Paris VI), Ecole Nationale des Ponts et Chaussées, University of Versailles.He is the author and co-author of several technical papers.Cyril Royere was born in France, in 1972. He received the M.S. degree in 1995 from the university of Reims. In 2002 he received the Ph.D. degree from the university of Technology of Compiegne. In his thesis, he describes the origins of the conflict which appears when combining of various sources of imperfect information within the framework of the belief theory. Since 2002, he is a researcher at INRETS, into the perception team of the LIVIC department (Laboratory on interactions between vehicles, Infrastructure and drivers) and works on automated highway and on on-board driving assistance systems. His main work deals with obstacles detection using data fusion. He is involved for multi-sensor fusion tasks in several European and French projects dealing with intelligent vehicles (CARSENSE, MICADO, ARCOS).He is the author and co-author of several technical papers.Dominique Gruyer was born in France, in 1969. He received the M.S. and Ph.D. degree respectively in 1995 and 1999 from the university of Technology of Compiëgne.Since 2001, he is a researcher at INRETS, into the perception team of the LIVIC department (Laboratory on interactions between vehicles, Infrastructure and drivers) and he works on the study and the development of multi-sensor/sources association, combination and fusion. His works enter into the conception of on-board driving assistance systems and more precisely on the carry out of multi-obstacle detection and tracking, extended perception, accurate localization, anti-collision system, collision mitigation. He is involved for multi-sensor fusion tasks in several European and French projects dealing with intelligent vehicles (CARSENSE, MICADO, ARCOS). He is a multi-sensor fusion expert for several companies, teaches at Orsay (Paris XI), Ecole Nationale des Ponts et Chaussées and University of Technologie of Compiëgne.He is the author and co-author of several technical papers.Didier Aubert was born in France, in 1963. He received the M.S. and Ph.D. degree respectively in 1985 and 1989 from the university of Grenoble. From 1989–1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was project leader of several projects dealing with computer vision (Multi-resolution, color, motion detection, 3D reconstruction, 3D location, Shape recognition, automatic shape modelling, object tracking), mobile robotic (calibration, roads following, free space computation) and manipulator robotic (calibration, automatic surface tracking). He was also working as an expert for companies on the face recognition, 3D location and roads following topics. He is currently a researcher at INRETS since 1995, manages the perception team of the LIVIC department and works on car traffic monitoring, crowd monitoring, incidents detection, automated highway and on on-board driving assistance systems. He is an image processing expert for several compagnies, teaches at Jussieu (Paris VI), Ecole Nationale des Ponts et Chaussées, Ecole Nationale Supérieure des Télécommunications, Orsay (Paris XI) and is at the editorial board of RTS (Research-Transport-Safety).He is the author and co-author of several technical papers and has participated to the redaction of the books named “Robotique mobile” and “la route automatisée.”     

Discrete Surfaces and Frontier Orders

Many applications require the extraction of an object boundary from a discrete image. In most cases, the result of such a process is expected to be, topologically, a surface, and this property might be required in subsequent operations. However, only through careful design can such a guarantee be provided. In the present article we will focus on partially ordered sets and the notion of n-surfaces introduced by Evako et al. to deal with this issue. Partially ordered sets are topological spaces that can represent the topology of a wide range of discrete spaces, including abstract simplicial complexes and regular grids. It will be proved in this article that (in the framework of simplicial complexes) any n-surface is an n-pseudomanifold, and that any n-dimensional combinatorial manifold is an n-surface. Moreover, given a subset of an n-surface (an object), we show how to build a partially ordered set called frontier order, which represents the boundary of this object. Similarly to the continuous case, where the boundary of an n-manifold, if not empty, is an (n−1)-manifold, we prove that the frontier order associated to an object is a union of disjoint (n−1)-surfaces. Thanks to this property, we show how topologically consistent Marching Cubes-like algorithms can be designed using the framework of partially ordered sets.X. Daragon is a Ph.D. student at ESIEE, A2SI laboratory. He received a DEA in computer science from Marne-La-Vallee University in 2000. His research focuses on order theory and its applications to image analysis and computer graphics, mainly in the field of 3D medical imaging (segmentation of the cerebral neo-cortex).Michel Couprie received his Ingénieur’s degree from the École Supérieure d’Ingénieurs en Électrotechnique et Électronique (Paris, France) in 1985 and the Ph.D. degree from the Pierre et Marie Curie University (Paris, France) in 1988. Since 1988 he has been working in ESIEE where he is an Associate Professor. He is a member of the Laboratoire Algorithmique et Architecture des Systèmes Informatiques, ESIEE, Paris, and of the Institut Gaspard Monge, Université de Marne-la-Vallée. His current research interests include image analysis and discrete mathematics.Gilles Bertrand received his Ingénieur’s degree from the École Centrale des Arts et Manufactures in 1976. Until 1983 he was with the Thomson-CSF company, where he designed image processing systems for aeronautical applications. He received his Ph.D. from the École Centrale in 1986. He is currently teaching and doing research with the Laboratoire Algorithmique et Architecture des Systèmes Informatiques, ESIEE, Paris, and with the Institut Gaspard Monge, Université de Marne-la-Vallée. His research interests are image analysis, pattern recognition, mathematical morphology and digital topology.     

Quasi-Linear Algorithms for the Topological Watershed

The watershed transformation is an efficient tool for segmenting grayscale images. An original approach to the watershed (Bertrand, Journal of Mathematical Imaging and Vision, Vol. 22, Nos. 2/3, pp. 217–230, 2005.; Couprie and Bertrand, Proc. SPIE Vision Geometry VI, Vol. 3168, pp. 136–146, 1997.) consists in modifying the original image by lowering some points while preserving some topological properties, namely, the connectivity of each lower cross-section. Such a transformation (and its result) is called a W-thinning, a topological watershed being an ultimate W-thinning. In this paper, we study algorithms to compute topological watersheds. We propose and prove a characterization of the points that can be lowered during a W-thinning, which may be checked locally and efficiently implemented thanks to a data structure called component tree. We introduce the notion of M-watershed of an image F, which is a W-thinning of F in which the minima cannot be extended anymore without changing the connectivity of the lower cross-sections. The set of points in an M-watershed of F which do not belong to any regional minimum corresponds to a binary watershed of F. We propose quasi-linear algorithms for computing M-watersheds and topological watersheds. These algorithms are proved to give correct results with respect to the definitions, and their time complexity is analyzed.Michel Couprie received his Ingénieurs degree from the École Supérieure dIngénieurs en Électrotechnique et Électronique (Paris, France) in 1985 and the Ph.D. degree from the Pierre et Marie Curie University (Paris, France) in 1988. Since 1988 he has been working in ESIEE where he is an Associate Professor. He is a member of the Laboratoire Algorithmique et Architecture des Systémes Informatiques, ESIEE, Paris, and of the Institut Gaspard Monge, Universit é de Marne-la-Vallée. His current research interests include image analysis and discrete mathematics.Laurent Najman received his Ph.D. of applied mathematics from Paris-Dauphine university and an Ingénieurs degree from the Ecole des Mines de Paris. After earning his Ingénieurs degree, he worked in the research laboratories of Thomson-CSF for three years, before joining Animation Science in 1995, as director of research and development. In 1998, he joined OcÉ Print Logic Technolgies, as senior scientist. Since 2002, he is associate professor with the A2SI laboratory of ESIEE, Paris. His current research interest is discrete mathematical morphology.Gilles Bertrand received his Ingénieurs degree from the École Centrale des Arts et Manufactures in 1976. Until 1983 he was with the Thomson-CSF company, where he designed image processing systems for aeronautical applications. He received his Ph. from the École Centrale in 1986. He is currently teaching and doing research with the Laboratoire Algorithmique et Architecture des Systémes Informatiques, ESIEE, Paris, and with the Institut Gaspard Monge, Université de Marne-la-Vallée. His research interests are image analysis, pattern recognition, mathematical morphology and digital topology.     

Adapted Total Variation for Artifact Free Decompression of JPEG Images

The widely used JPEG lossy baseline coding system is known to produce, at low bit rates, blocking effects and Gibbs phenomenon. This paper develops a method to get rid of these artifacts without smoothing images and without removing perceptual features. This results in better looking pictures and improved PSNR. Our algorithm is based on an adapted total variation minimization approach constrained by the knowledge of the input intervals the unquantized cosine coefficients belong to. In this way, we reconstruct an image having the same quantized coefficients than the original one, but which is minimal in term of the total variation. This discourages blocking effects and Gibbs phenomenon to appear while edges are kept as sharp as possible. Although the proposed subgradient method is converging in infinite time, experiments show that best results are obtained with a very few number of iterations. This leads to a simple and fast algorithm that may be applied to the great set of JPEG images to decompress them more efficiently.This work was also supported in part by CNES, 18 avenue E. Belin, 31055 Toulouse Cedex, France and Science Pratique SA, 47 avenue Carnot, 94230 Cachan, France under Grant 762/00/CNES/8319; by CMLA, ENS Cachan, 61 avenue du Président Wilson, 94235 Cachan Cedex, France; by DOLabs, 3 rue Nationale, 92100 Boulogne-Billancourt, France and by MAP5, UFR mathématiques et informatique, Université Paris 5, 45 rue des Saints Pères, 75270 Paris Cedex 06, France. François Alter was at École Normale Supérieure Ulm in Paris from 1998 to 2003, and entered the Corps des Mines attached to the French minister in charge of industry in 2003. He received M.Sc. degree in Pure Mathematics from Paris 6 University in 2001. Since 2002, he has been preparing his Ph.D. in Image Processing and Analysis at CMLA in Cachan, France. His research interests are Geometric Partial Differential Equations and Stochastic Perception Theory. Sylvain Durand received his PhD in applied mathematics, in 1993, from Paris-Dauphine University, France. In 1994 and 1995, he held a postdoctoral position at Washington University of St. Louis, Missouri. He is currently assistant professor at Jules Verne University of Picardie, France. His research interests include mathematical aspects of image processing. Jacques Froment received the Ph.D. degree in applied mathematics from Paris-Dauphine University, France, in 1990. During the academic year 1990/1991, he was an associate research scientist at the Courant Institute of Mathematical Sciences in NYUs computer science department. From 1991 to 2002, he was an assistant professor in the department of mathematics at Paris 5 University, France. He is currently professor of applied mathematics at the University of Bretagne Sud, Vannes, France. His research interests include mathematical models in computer vision and representation of meaningful information with applications to image compression and restoration.This revised version was published online in June 2005 with correction to CoverDate     

Extracting Meaningful Curves from Images

Since the beginning, Mathematical Morphology has proposed to extract shapesfrom images as connected components of level sets. These methods have proved veryefficient in shape recognition and shape analysis. In this paper, we present an improved method to select the most meaningful level lines (boundaries of level sets) from an image. This extraction can be based on statistical arguments, leading to a parameter free algorithm. It permits to roughly extract all pieces of level lines of an image, that coincide with pieces of edges. By this method, the numberof encoded level lines is reduced by a factor 100, without any loss of shape contents. In contrast to edge detection algorithms or snakes methods, such a level lines selection method delivers accurate shape elements, without user parameter since selection parameters can be computed by the Helmholtz Principle. The paper aims at improving the original method proposed in [10]. We give a mathematicalinterpretation of the model, which explains why some pieces of curve are overdetected. We introduce a multiscale approach that makes the method more robust to noise. A more local algorithm is introduced, taking local contrast variations into account. Finally, we empirically prove that regularity makes detection more robust but does not qualitatively change the results.Frédéric Cao graduated from the École Polytechnique (France), and obtained his Ph.D. in 2000 at École Normale Supérieure de Cachan. From 2001, he has been with Irisa (Inria Rennes). His research interests are still image and video analysis by geometrical methods, including partial differential equations and statistical methods.Pablo Musé was born in Montevideo, Uruguay, in 1975. He received the Electrical Engineer degree from the Universidad de la Repblica, Uruguay, in 1999, and the DEA (M.Sc.) in Mathematics, Vision and Learning from the École Normale Supérieure de Cachan, France, in 2001. He has obtained a Ph.D. in Applied Mathematics in 2004 in ENS Cachan, where he currently has a researcher position.Frédéric Sur was born in 1976. He studied mathematics at École Normale Supérieure de Cachan from 1997 to 2001 and received the DEA Mathématiques, Vision, Apprentissage. He obtained his Ph.D. thesis in 2004 and now he has a post doc position in LORIA/CNRS.     

On Topological Watersheds

In this paper, we investigate topological watersheds (Couprie and Bertrand, 1997). One of our main results is a necessary and sufficient condition for a map G to be a watershed of a map F, this condition is based on a notion of extension. A consequence of the theorem is that there exists a (greedy) polynomial time algorithm to decide whether a map G is a watershed of a map F or not. We introduce a notion of separation between two points of an image which leads to a second necessary and sufficient condition. We also show that, given an arbitrary total order on the minima of a map, it is possible to define a notion of degree of separation of a minimum relative to this order. This leads to a third necessary and sufficient condition for a map G to be a watershed of a map F. At last we derive, from our framework, a new definition for the dynamics of a minimum.Gilles Bertrand received his Ingénieurs degree from the École Centrale des Arts et Manufactures in 1976. Until 1983 he was with the Thomson-CSF company, where he designed image processing systems for aeronautical applications. He received his Ph.D. from the École Centrale in 1986. He is currently teaching and doing research with the Laboratoire Algorithmique et Architecture des Systémes Informatiques, ESIEE, Paris, and with the Institut Gaspard Monge, Université de Marne-la-Vallée. His research interests are image analysis, discrete topology and mathematical morphology.     

Exhaustive analysis and simulation for distributed systems,both sides of the same coin

This paper presents exhaustive analysis and simulation for distributed systems validation. Exhaustive analysis makes possible to detect quickly several types of errors, for instance, unspecified reception of signals, errors in timer management, deadlock, errors in precedence, etc. But, in general, exhaustive analysis can only be applied to a simplified model of the distributed system due to the state explosion problem. On the other hand, simulation permits accurate tests and confronts the distributed system to complex situations. We think both forms of validation are complementary. Validation was done on systems specified in the SDL language, using OVAL, a tool for specification validation developed at CNET, Paris A. This tool allows exhaustive analysis and simulation of SDL specified systems. We illustrate our results with several examples. Ana R. Cavalli received the Doctorat d'Etat ès Sciences Mathematiques in 1984, from the University of Paris VII, France. From 1975 to 1981 she was associate professor in the Computer Science Department, at the Universidad Central de Venezuela, Caracas. In 1981, she joined the Laboratoire d'Informatique Theorique et Programmation of the C.N.R.S., Paris, where she worked on automatic proofs methods for temperal logics and their applications to the specification and verification of protocols. She is now involved in the Concurrency Communication and Cooperation Project. (C.N.R.S.). In 1985, she joined the Department of Langages et Systèmes de Commutation, at the CNET (Centre National d'Etudes des Telecommunications), Paris, where she works on software engineering and formal specification techniques. His research interests are in formal specification techniques.and verification of distributed systems, including logics and models for parallel systems. Etienne Paul received the ingenieer degree in 1974, from the Ecole Polytechnique, France, and the telecommunications ingenieer degree in 1976 from the Ecole Nationale Superieure des Telecommunications, France. He joined the Department of Langages et Systèmes de Commutation, at the CNET (Centre National d'Etudes des Telecommunications), in 1977. From 1977 to 1981, he worked on the development of telecommunications systems, and since 1982, on software engineering and formal specification techniques. His first interest in formal specification techniques has been in the field of algebraic data types and logic programming. Now he is mainly working on SDL language and is responsible for the OVAL project. During the RACE definition phase, he has also worked on the SPECS project.     

A Unified Framework for Detecting Groups and Application to Shape Recognition

A unified a contrario detection method is proposed to solve three classical problems in clustering analysis. The first one is to evaluate the validity of a cluster candidate. The second problem is that meaningful clusters can contain or be contained in other meaningful clusters. A rule is needed to define locally optimal clusters by inclusion. The third problem is the definition of a correct merging rule between meaningful clusters, permitting to decide whether they should stay separate or unite. The motivation of this theory is shape recognition. Matching algorithms usually compute correspondences between more or less local features (called shape elements) between images to be compared. Each pair of matching shape elements leads to a unique transformation (similarity or affine map.) The present theory is used to group these shape elements into shapes by detecting clusters in the transformation space. Frédéric Cao graduated from the Ecole Polytechnique in 1995 and obtained a PhD in applied mathematics in Ecole Normale Supérieure de Cachan in 2000. He defended his “Habilitation à diriger des recherches" in 2004. His research interests include partial differential equations for image and shape filtering, but also statistical approaches to shape recognition and data analysis, or motion analysis. Julie Delon was born in France in 1978. During the period 1997–2001, she has studied applied mathematics at the Ecole Normale Supérieure de Cachan. From 2001 to 2004, she prepared a Ph.D. thesis in image analysis at the CMLA (Cachan, France), and defended it in December 2004. She is currently a research scientist with CNRS at Télécom Paris. Agnès Desolneux was born in France in 1974. She defended her PhD thesis in applied mathematics in 2000 under the direction of Jean-Michel Morel at the ENS Cachan. She is currently CNRS researcher at the MAP5, University Paris 5. She is working on statistical methods in image analysis. Web page: http://www.math-info.univ-paris5.fr/~desolneux/ Pablo Musé was born in Montevideo, Uruguay, in 1975. He received the Electrical Engineer degree from the Universidad de la República, Uruguay, in 1999, and the DEA in Mathematics, Vision and Learning from the Ecole Normale Supérieure de Cachan, France, in 2001. In 2004 he obtained his Ph.D. in Applied Mathematics, also from ENS Cachan, where he had a researcher position until May 2005. Since then he has been with Cognitech Inc., Pasadena, CA, USA. Frédéric Sur was born in 1976. He is a former student of école Normale Supérieure de Cachan, France. In 2004, he received his PhD degree in applied mathematics and image analysis from Université Paris Dauphine. He is now an assistant professor at école des Mines de Nancy (France) and with Loria laboratory.     

Eigenvalues of dynamic max-min systems

Discrete event dynamic systems are studied in which the time evolution depends on the max-, min-, and the summation operation simultaneously. Specifically, necessary and sufficient conditions are given under which the operator which characterizes the evolution of such a system has an eigenvalue and eigenvector(s). Numerical algorithms to calculate these quantities are also provided.Most of the research described in this paper was done while at École des Mines de Paris in Fontainebleau, Centre d'Automatique et Informatique, France, during the summer of 1989.     

A new method for implementing moment functions in a CMOS retina

We present in this paper a new method for implementing geometric moment functions in a CMOS retina. The principle is based on the similarity between geometric moment equations and the measurement of the correlation value between an image to analyze and a range of grey levels. The latter is approximated by a binary image called mask using a dithering algorithm in order to reduce hardware implementation cost. The correlation product between the mask and the image under analysis gives an approximated value of the geometric moment with an error less than 1% of the exact value. Finally, the results obtained by our approach have been applied to an object localization application and the localization error due to the approximated moment values reported. Olivier Aubreton was born in Vichy on August 31, 1973. He obtained the agrégation examination in June 2000 and received the D.E.A. degree (equivalent to a master degree) in image processing in June 2001. He is currently a lecturer working towards a Ph. D. degree at Laboratory LE2I in the IUT of Le Creusot in Burgundy. His research interests include the design, development implementation, and testing of silicon retinas for pattern matching and pattern recognition. Lew F.C. Lew Yan Voon received his Ph.D. degree in Computer Aided Design of VLSI circuits from Montpellier University, France, in March 1992. Since September 1993, he has been first assistant professor and then associate professor at the University of Burgundy. His research interests lie in the field of pattern recognition and in the design of silicon retinas in standard CMOS technology for real-time inspection by machine vision. Bernard Lamalle was born in Autun on May 1, 1946. He obtained the Ph.D. degree in 1973 from the Université de Bourgogne in Dijon. During 1980 to 2000 he has been Maître de conférences at the IUT of Le Creusot in Bourgogne. He joined the image processing team of laboratory Le2i in 1992. Since 2000, he has been appointed full professor of the University of Bourgogne. His field of interest is principally the study and design of silicon retinas dedicated to industrial control. He has in charge some industrial contracts in the field of quality control by artificial vision and he holds two patents in the field of image processing and smart sensors. Guy Cathébras was born in Uzès, France, in 1961. He received the French engineer degree from the Ecole Nationale Supérieure de l'Electronique et de ses Applications, Cergy, France, in 1984 and the Diplôme de Doctorat de l'Université de Montpellier, France, in 1990. Since 1992 he is an assistant professor of microelectronics at the Institut des Sciences de l'Ingénieur de Montpellier. His current research interests include the design of imagers and silicon retinas using standard CMOS technologies.     

Globally Optimal Geodesic Active Contours

An approach to optimal object segmentation in the geodesic active contour framework is presented with application to automated image segmentation. The new segmentation scheme seeks the geodesic active contour of globally minimal energy under the sole restriction that it contains a specified internal point p_int. This internal point selects the object of interest and may be used as the only input parameter to yield a highly automated segmentation scheme. The image to be segmented is represented as a Riemannian space S with an associated metric induced by the image. The metric is an isotropic and decreasing function of the local image gradient at each point in the image, encoding the local homogeneity of image features. Optimal segmentations are then the closed geodesics which partition the object from the background with minimal similarity across the partitioning. An efficient algorithm is presented for the computation of globally optimal segmentations and applied to cell microscopy, x-ray, magnetic resonance and cDNA microarray images.Ben Appleton received degrees in engineering and in science from the University of Queensland in 2001 and was awarded a university medal. In 2002 he began a Ph.D at the University of Queensland in the field of image analysis. He is supported by an Australian Postgraduate Award and the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Mathematical and Information Sciences. He has been a teaching assistant in image analysis at the University of Queensland since 2001. He has also contributed 10 research papers to international journals and conferences and was recently awarded the prize for Best Student Paper at Digital Image Computing: Techniques and Applications. His research interests include image segmentation, stereo vision and algorithms.Hugues Talbot received the engineering degree from École Centrale de Paris in 1989, the D.E.A. (Masters) from University Paris VI in 1990 and the Ph.D from École des Mines de Paris in 1993, under the guidance of Dominique Jeulin and Jean Serra. He has been affiliated with the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Mathematical and Information Sciences since 1994. He has worked on numerous applied projects in relation with industry, he has contributed more than 30 research papers in international journals and conferences and he has co-edited two sets of international conference proceedings on image analysis. He now also teaches image processing at the University of Sydney, and his research interest include image segmentation, linear structure analysis, texture analysis and algorithms.     

Stable methods for recognizing acronym-expansion pairs: from rule sets to hidden Markov models

A significant portion of currently available documents exist in the form of images, for instance, as scanned documents. Electronic documents produced by scanning and OCR software contain recognition errors. This paper uses an automatic approach to examine the selection and the effectiveness of searching techniques for possible erroneous terms for query expansion. The proposed method consists of two basic steps. In the first step, confused characters in erroneous words are located and editing operations are applied to create a collection of erroneous error-grams in the basic unit of the model. The second step uses query terms and error-grams to generate additional query terms, identify appropriate matching terms, and determine the degree of relevance of retrieved document images to the user's query, based on a vector space IR model. The proposed approach has been trained on 979 document images to construct about 2,822 error-grams and tested on 100 scanned Web pages, 200 advertisements and manuals, and 700 degraded images. The performance of our method is evaluated experimentally by determining retrieval effectiveness with respect to recall and precision. The results obtained show its effectiveness and indicate an improvement over standard methods such as vectorial systems without expanded query and 3-gram overlapping. Youssef Fataicha received his B.Sc. degree from Université de Rennes1, Rennes, France, in 1982. In 1984 he obtained his M.Sc. in computer science from Université de Rennes1, France. Between 1984 and 1986 he was a lecturer at the Université de Rennes1, France. He then served as engineer, from 1987 to 2000, at {Office de l'eau potable et de l'électricité} in Morocco. Since 2001 has been a Ph.D. student at the {école de Technologie Supérieure de l'Université du Québec} in Montreal, Québec, Canada. His research interests include pattern recognition, information retrieval, and image analysis. Mohamed Cheriet received his B.Eng. in computer science from {Université des Sciences et de Technologie d'Alger} (Bab Ezouar, Algiers) in 1984 and his M.Sc. and Ph.D., also in computer science, from the University of Pierre et Marie Curie (Paris VI) in 1985 and 1988, respectively. Dr. Cheriet was appointed assistant professor in 1992, associate professor in 1995, and full professor in 1998 in the Department of Automation Engineering, {école de Technologie Supérieure} of the University of Québec, Montreal. Currently he is the director of LIVIA, the Laboratory for Imagery, Vision and Artificial Intelligence at ETS, and an active member of CENPARMI, the Centre for Pattern Recognition and Machine Intelligence. Professor Cheriet's research focuses on mathematical modeling for signal and image processing (scale-space, PDEs, and variational methods), pattern recognition, character recognition, text processing, document analysis and recognition, and perception. He has published more than 100 technical papers in these fields. He was the co-chair of the 11th and the 13th Vision Interface Conferences held respectively in Vancouver in 1998 and in Montreal in 2000. He was also the general co-chair of the 8th International Workshop on Frontiers on Handwriting Recognition held in Niagara-on-the-Lake in 2002. He has served as associate editor of the International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI) since 2000. Dr. Cheriet is a senior member of IEEE. Jian Yun Nie is a professor in the computer science department (DIRO), Université de Montreal, Québec, Canada. His research focuses on problems related to information retrieval, including multilingual and multimedia information retrieval, as well as natural language processing. Ching Y. Suen received his M.Sc. (Eng.) from the University of Hong Kong and Ph.D. from the University of British Columbia, Canada. In 1972 he joined the Department of Computer Science of Concordia University, where he became professor in 1979 and served as chairman from 1980 to 1984 and as associate dean for research of the Faculty of Engineering and Computer Science from 1993 to 1997. He has guided/hosted 65 visiting scientists and professors and supervised 60 doctoral and master's graduates. Currently he holds the distinguished Concordia Research Chair in Artificial Intelligence and Pattern Recognition and is the Director of CENPARMI, the Centre for Pattern Recognition and Machine Intelligence.Professor Suen is the author/editor of 11 books and more than 400 papers on subjects ranging from computer vision and handwriting recognition to expert systems and computational linguistics. A Google search on “Ching Y. Suen” will show some of his publications. He is the founder of the International Journal of Computer Processing of Oriental Languages and served as its first editor-in-chief for 10 years. Presently he is an associate editor of several journals related to pattern recognition.A fellow of the IEEE, IAPR, and the Academy of Sciences of the Royal Society of Canada, he has served several professional societies as president, vice-president, or governor. He is also the founder and chair of several conference series including ICDAR, IWFHR, and VI. He has been the general chair of numerous international conferences, including the International Conference on Computer Processing of Chinese and Oriental Languages in August 1988 held in Toronto, International Conference on Document Analysis and Recognition held in Montreal in August 1995, and the International Conference on Pattern Recognition held in Québec City in August 2002.Dr. Suen has given 150 seminars at major computer companies and various government and academic institutions around the world. He has been the principal investigator of 25 industrial/government research contracts and is a grant holder and recipient of prestigious awards, including the ITAC/NSERC award from the Information Technology Association of Canada and the Natural Sciences and Engineering Research Council of Canada in 1992 and the Concordia “Research Fellow” award in 1998.     

Behavior of the Laplacian of Gaussian Extrema

This paper analyses the behavior in scale space of linear junction models (L, Y and X models), nonlinear junction models, and linear junction multi-models. The variation of the grey level is considered to be constant, linear or nonlinear in the case of linear models and constant for the other models. We are mainly interested in the extrema points provided by the Laplacian of the Gaussian function. Moreover, we show that for infinite models the Laplacian of the Gaussian at the corner point is not always equal to zero.Salvatore Tabbone received his Ph.D. in computer science from the Institut National Polytechnique de Lorraine (France) in 1994. He is currently an assistant professor at the University of Nancy2 (France) and a member of the QGAR research project on graphics recognition at the LORIA-INRIA research center. His research interests include computer vision, pattern recognition, content-based image retrieval, and document analysis and recognition.Laurent Alonso was a student of ENS Ulm from 1987 to 1991, he received the Ph.D. degree in Computer Science from the University of Paris XI, Orsay, France in 1992. From 1991 to 1995 he served as lecturer in the University of Nancy I (France). Actually, he is full researcher in INRIA (France). His research interests include realistic rendering, geometric algorithms and combinatorics.Djemel Ziou received the BEng Degree in Computer Science from the University of Annaba (Algeria) in 1984, and Ph.D. degree in Computer Science from the Institut National Polytechnique de Lorraine (INPL), France in 1991. From 1987 to 1993 he served as lecturer in several universities in France. During the same period, he was a researcher in the Centre de Recherche en Informatique de Nancy (CRIN) and the Institut National de Recherche en Informatique et Automatique (INRIA) in France. Presently, he is full Professor at the department of computer science at the University of Sherbrooke in Canada. He has served on numerous conference committees as member or chair. He heads the laboratory MOIVRE and the consortium CoRIMedia which he founded. His research interests include image processing, information retrieval, computer vision and pattern recognition.     

A Framework for the Generation of Adaptive Courses Based on Semantic Metadata

This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model.John Freddy Duitama received his M.Sc. degree in system engineering from the University of Antioquia -Colombia (South America). He is currently a doctoral candidate in the GET – Institut National des Télécommunications, Evry France. This work is sponsored by the University of Antioquia, where he is assistant professor.His research interest includes semantic web and web-based learning systems, educational metadata and learning objects.Bruno Defude received his Ph.D. in Computer Science from the University of Grenoble (I.N.P.G) in 1986. He is currently Professor in the Department of Computer Science at the GET - Institut National des Télécommunications, Evry France where he leads the SIMBAD project (Semantic Interoperability for MoBile and ADaptive applications).His major field of research interest is databases and semantic web, specifically personalized data access, adaptive systems, metadata, interoperability and semantic Peer-to-peer systems with elearning as a privileged application area.He is a member of ACM SIGMOD.Amel Bouzeghoub received a degree of Ph.D. in Computer Sciences at Pierre et Marie Curie University, France.In 2000, she joined the Computer Sciences Department of GET-INT (Institut National des Telecommunications) at Evry (France) as an associate professor.Her research interests include topics related to Web-based Learning Systems, Semantic Metadata for learning resources, Adaptive Learning Systems and Intelligent Tutoring Systems.Claire Lecocq received an Engineer Degree and a Ph.D. in Computer Sciences respectively in 1994 and 1999. In 1997, she joined the Computer Sciences Department at GET-INT (Institut National des Télécommunications) of Evry, France, as an associate professor. Her first research interests included spatial databases and visual query languages. She is now working on adaptive learning systems, particularly on semantic metadata and user models.     

Joint Adoption of QoS Schemes for MPEG Streams

Indiscriminated packet discards strongly degrade the quality perceived by end users of MPEG video transmissions. This paper investigates different Quality of Service (QoS) schemes and the tradeoffs of jointly adopting such schemes to improve the delivery quality of an MPEG stream. From an analytical model, we evaluate the impact of frame losses on the quality of MPEG streams and on the waste of network resources. Our assessment considers issues such as the use of redundancy by applying a Forward Error Correction (FEC) scheme to tolerate losses, the changing of the compression factor in MPEG encoding, the unequal protection of MPEG frames in a Differentiated Services environment, and how to evaluate the impact of network losses onto application quality. Results provide predicted bounds on the quality to be expected by end users as well as guidelines on how to take the best advantage from the joint adoption of the investigated QoS schemes.Artur Ziviani received the B.Sc. degree in Electronics Engineering in 1998 and the M.Sc. degree in Electrical Engineering (with emphasis in Computer Networking) in 1999, both from the Federal University of Rio de Janeiro (UFRJ), Brazil. In December 2003, he received the Ph.D. degree in Computer Science from the University Pierre et Marie Curie (Paris 6), Paris, France, where he has also been a lecturer during the 2003–2004 academic year. Since September 2004, he is with the National Laboratory for Scientific Computing (LNCC), located in Petr'opolis, Brazil. His major research interests are quality of service, mobile and wireless computing, Internet measurements, and grid computing.Bernd E. Wolfinger has been with the Computer Science Department of Hamburg University since 1981, where he is presently heading the Telecommunications and Computer Networks (TKRN) Subdivision. He has degrees from Universit Claude-Bernard, Lyon (Matrise, 74), University of Karlsruhe (Diploma, Mathematics 75; Ph.D., Comp. Sc. 79) and has spent long-term sabbaticals at IBM Research, Yorktown Heights, N.Y. (85), Internat. Computer Science Institute, Berkeley, Ca. (91,96), as well as at Universit P. et M. Curie, Paris (01). Dr. Wolfinger is active in Networking research since 1975, has been responsible for numerous conference organizations and has served on a variety of TPCs. He has been an editor of books and special issues of journals and has published more than 100 papers in areas such as High-speed & Mobile Networks, Real-time Communications, Traffic Engineering, Modeling, Performance Evaluation and QoS Management.Jos'e Ferreira de Rezende received the B.Sc. and M.Sc. degrees in Electronic Engineering from the Universidade Federal do Rio de Janeiro (UFRJ) in 1988 and 1991, respectively. He received the Ph.D. degree in Computer Science from the Universit Pierre et Marie-Curie, Paris, France in 1997. He was an associate researcher at LIP6 (Laboratoire dInformatique de Paris 6) during 1997. Since 1998 he is an Associate Professor at UFRJ. His research interests are in distributed multimedia applications, multipeer communication, performance evaluation and QoS aspects of high-speed, wireless and sensor networks.Otto Carlos M.B. Duarte was born in Rio de Janeiro, Brazil, on October 23, 1953. He received the Electronic Engineer degree and the M.Sc. degree in Electrical Engineering from Universidade Federal do Rio de Janeiro, Brazil, in 1976 and 1981, respectively, and the Dr. Ing. degree from ENST/ Paris, France, in 1985. Since 1978 he is a Professor at Universidade Federal do Rio de Janeiro. From January 1992 to June 1993 he has worked at MASI Laboratory in Paris 6 University. In 1995, he has spent three months at International Computer Science Institute (ICSI) associated to the University of California at Berkeley. Presently, he is heading the computer network group (Grupo de Teleinformitica e Automao—GTA). His major research interests are in high speed communications, mobility, security and QoS guarantees.Serge Fdida is a professor at the University Pierre et Marie Curie (Paris) since 1991. He received the Doctorat de 3eme Cycle in 1984, and the Habilitation a Diriger des Recherches specializing in Modelling of computer networks in 1989 from the University Pierre et Marie Curie. From 1989 to 1995, he was a Full Professor to the University Rene Descartes (Paris). His research interests are in the area of high speed networking, pervasive communication, resource management and performance analysis. He is heading the Network and Performance group of the LIP6 Laboratory (CNRS-University of Paris 6). He was a Visiting Scientist at IBM Research during the 1990/91 academic year. He was the chairman (or co-chair) of the following events: IFIP Modelling Techniques and Tools 87, IFIP High Performance Networking 94 (HPN 94), Performance of Data Communication 95 (PCN 95) and European Conference on Multimedia Applications, Services and Techniques 97 (ECMAST 97), Networked Group Communication (NGC 99) and IFIP Networking 2000. He was the editor of the proceedings of these conferences and is the author of a book on performance evaluation and a book on Networking. He is involved in many research projects in High Performance Networking in France and Europe. He was heading the RHDM Action in France for 8 years and the COST264 Action in Europe (98 02). He belongs to the FP6 network of Excellence ENEXT. He is a senior member of IEEE, a member of ACM and also involved in two IFIP working groups on networking. He is also the Co-Director of EURONETLAB, a joint laboratory established in 2001, between University Paris 6, CNRS, THALES and 6WIND, developing research and development work on QoS Routers and Radio Routers.     

Computer enhanced assessment of case-notes in studies of psychopathology: The example of an autistic subject

Case report notes on encounters and exchanges between a clinician and a patient are a rich and irreplaceable source of information in studies of psychopathology. The analysis and exploitation of these notes may be considerably enhanced by transcribing the original notes to computer text files, and subsequently submitting these files to computerized reading. This makes it possible to take account both of qualitative and quantitative features of the behaviour and events described in the notes. Notes taken during encounters with an autistic subject were analyzed in this way. The subject's verbal and gestural repertoires were identified, together with their relative frequencies, their principal associations, and their trends over successive encounters for the items described. The method also made it possible to specify the way in which the Observer was involved in encounters, and his role in them. Major conclusions were that the autistic subject distinctly avoided triadic situations, preferentially pronounced words and phonemes similar to those of his own name, and did not distinguish between the representations he had of persons, objects, places, gestures and words. He also failed to distinguish between the representation he had of himself and of his own name.J.-M. Vidal (Docteur d'Etat, 1976) is Chargé de Recherche CNRS. He studied the behavioral process of attachment in animals before studying discontinuities of mind between animals and humans, and psychopathological processes of non-attachment in autistic subjects. He has published, Motivation et attachement, inEncyclopédie de la Pléiade, Paris: Gallimard, 1987, and Evolution des psychismes et évolution des organismes, inDarwinisme et Société, Paris: Presses Universitaires de France, 1992. R. Quris is Ingénieur de Recherche CNRS. He specializes in the application of linear algebraic models in multivariate analysis which he originally applied to behavioral data from animals. More recently, he extended these applications, with his ANATEXT program, to the analysis of lexical data drawn from clinical dialogues. He is also the author of other multivariate analysis programs:Calmat Matrix Computation Tool, v. 1.4 (1993), Exeter Software, 100 North Country Road, Setauket, NY 11733, andGTABM, gestionnaire de tableaux multiples, v. 2.0 (1994), CNRS 74E, rue de Paris, 3069 Rennes, France.     

Multiresolution volumetric 3D object reconstruction for collaborative interactions

Within the framework of collaborative interactions with 3D numerical copies of real objects inserted in virtual environments, this paper tackles the issue of 3D object reconstruction from multiple calibrated cameras. After examining the various constraints related to collaborative systems, we propose comprehensive, state of the art 3D reconstruction techniques. The main families of approaches are here identified, described, and discussed in detail. An analysis of the literature shows that there is a lack of methods that are able to respond to the needs of the collaborative interaction applications, and that perform adequately in terms of computation time and reconstruction accuracy. Accordingly, we propose a new multiresolution volumetric approach that is able to obtain numerical copies of real objects at multiple resolutions. Experimental results demonstrate that the proposed approach provides accurate reconstructions at reasonable, interactive computation times. The use of the proposed approach for progressive insertion of reconstructed objects in the prototype interfaces MOWGLI and Spin-3D developed by FranceTelecom R&D is also illustrated. The text was submitted by the authors in English. Rachid Guerchouche. Was born in Algeria in 1979. He received an Engineer Degree in electronics from the National Polytechnic School of Algiers, Algeria in June 2004, and a research Masters Degree in Virtual Reality and Complex Systems Engineering from Université Evry-Val d’Essonne (France) in June 2005. He is currently a PhD student jointly in the ARTEMIS Department at TELECOM & Management SudParis and in the VIA Project Unit of the IRIS Laboratory at France Télécom R&D. Olivier Bernier. Was born in 1964. He received the diploma of the Ecole Polytech-nique (Palaiseau, France) in 1986 and the diploma of the Ecole Nationale Supérieure des Télécommunications (Paris, France) in 1988. Since this date, he has worked as a Research Engineer at Orange Labs-FT R&D, the research center of France Telecom. His areas of interest are computer vision, statistical learning and pattern recognition, in particular applied to advanced human machine interfaces. Titus Zaharia. Received an Engineer Degree in Electronics and the Masters Degree in Electronics from University POLITEHNICA (Bucharest, Romania) in 1995 and 1996, respectively. In 2001, he obtained a PhD degree in Mathematics and Computer Science from University Paris V—René Descartes (Paris, France). He then joined the ARTEMIS Department at TELECOM & Management SudParis as a research engineer, and became an Associate Professor in 2002. His research interests concern visual content indexing and coding, and include feature extraction, image and video segmentation, motion detection and estimation, 2D/3D reconstruction, virtual character modelling and animation, virtual/augmented reality, digital interactive TV, calibration techniques, and color image processing. Titus Zaharia is a member of SPIE.     

Image Decomposition into a Bounded Variation Component and an Oscillating Component

We construct an algorithm to split an image into a sum u + v of a bounded variation component and a component containing the textures and the noise. This decomposition is inspired from a recent work of Y. Meyer. We find this decomposition by minimizing a convex functional which depends on the two variables u and v, alternately in each variable. Each minimization is based on a projection algorithm to minimize the total variation. We carry out the mathematical study of our method. We present some numerical results. In particular, we show how the u component can be used in nontextured SAR image restoration.Jean-François Aujol graduated from 1 Ecole Normale Supérieure de Cachan in 2001. He was a PHD student in Mathematics at the University of Nice-Sophia-Antipolis (France). He was a member of the J.A. Dieudonné Laboratory at Nice, and also a member of the Ariana research group (CNRS/INRIA/UNSA) at Sophia-Antipolis (France). His research interests are calculus of variations, nonlinear partial differential equations, numerical analysis and mathematical image processing (and in particular classification, texture, decomposition model, restoration). He is Assistant Researcher at UCLA (Math Department).Gilles Aubert received the These dEtat es-sciences Mathematiques from the University of Paris 6, France, in 1986. He is currently professor of mathematics at the University of Nice-Sophia Antipolis and member of the J.A. Dieudonne Laboratory at Nice, France. His research interests are calculus of variations, nonlinear partial differential equations and numerical analysis; fields of applications including image processing and, in particular, restoration, segmentation, optical flow and reconstruction in medical imaging.Laure Blanc-Féraud received the Ph.D. degree in image restoration in 1989 and the Habilitation á Diriger des Recherches on inverse problems in image processing in 2000, from the University of Nice-Sophia Antipolis, France. She is currently director of research at CNRS in Sophia Antipolis. Her research interests are inverse problems in image processing by deterministic approach using calculus of variation and PDEs. She is also interested in stochastic models for parameter estimation and their relationship with the deterministic approach. She is currently working in the Ariana research group (I3S/INRIA) which is focussed on Earth observation.Antonin Chambolle studied mathematics and physics at the Ecole normale Supérieure in Paris and received the Ph.D. degree in applied mathematics from the Université de Paris-Dauphine in 1993. Since then he has been a CNRS researcher at the CEREMADE, Université de Paris-Dauphine, and, for a short period, a researcher at the SISSA, Trieste, Italy. His research interest include calculus of variations, with applications to shape optimization, mechanics and image processing.     

Reciprocal Systems Based on Planar Elements: Morphology and Design Explorations

The concept of transferring forces in a reciprocal way has always been related to the use of timber beams, that is, elongated elements. However, planar components can also be considered; circular tiles, squares, triangles and more articulated or irregular geometrical shapes are all valid alternatives. This report proposes an initial exploration of reciprocal systems based on planar elements in order to guide further morphological studies. It also presents some prototypes, which were developed by the students of the École des Ponts in Paris during two design workshops run in 2012 and 2013.