Cyril Meurie

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The problem described in this paper consists in re-identifying moving people in different sites which are completely covered with non-overlapping cameras. Our proposed framework relies on the spectral classification of the appearance-based signatures extracted from the detected person in each sequence. We first propose a new feature called(More)
In this paper, we describe a new scheme to color image segmentation which is based on supervised pixel classification methods. Using color pixel classification alone does not extract accurately enough color regions, so we suggest to use a strategy based on four steps in different color spaces: simplification, pixel classification, marker extraction and(More)
The processing of color images has become a major field of interest, however the direct extension of their gray scale counterparts is not always possible since there is no natural ordering of color vectors. Mathematical morphology has to face with this problem since it needs a complete lattice which is generally based on a conditional ordering. We propose(More)
This paper presents a graph-based ordering scheme of color vectors. A complete graph is defined over a filter window and its structure is analyzed to construct an ordering of color vectors. This graph-based ordering is constructed by finding a Hamiltonian path across the color vectors of a filter window by a two-step algorithm. The first step extracts, by(More)
This paper is focused on real time detection of satellite reception state. In constrained environment, such as urban areas, GNSS signals can be received directly, reflected or blocked by obstacles (building, vegetation, etc) and can lead to an error or a lack of positioning. This paper proposes to characterize the GNSS signals reception environment using(More)
In this paper, a new learning method is proposed to build Support Vector Machines (SVM) Binary Decision Function (BDF) of reduced complexity, efficient generalization and using an adapted hybrid color space. The aim is to build a fast and efficient SVM classifier of pixels. The Vector Quantization (VQ) is used in our learning method to simplify the training(More)
The combination of classifiers has been proposed as a method allowing to improve the quality of recognition systems as compared to a single classifier. This paper describes a segmentation scheme based on a combination of pixel classifications. The aim of this paper is to show the influence of the neighborhood information and of the number of classifiers(More)
Microscopic cellular image segmentation schemes must be efficient for reliable analysis and fast to process huge quantity of images. Recent studies have focused on improving segmentation quality. Several segmentation schemes have good quality but processing time is too expensive to deal with a great number of images per day. For segmentation schemes based(More)
We present in this paper a system for passengers counting in buses based on stereovision. The objective of this work is to provide a precise counting system and adapted to buses environment. The processing chain corresponding to this counting system involves several blocks dedicated to the detection, segmentation, tracking and counting. From original(More)
In this paper, a new graph-based ordering of color vectors is presented for mathematical morphology purposes. An attractive propoerty of the proposed ordering is its color space independence. A complete graph is defined over a filter window and its structure is analyzed to construct an ordering of color vectors by finding a Hamiltonian path in a two-step(More)