Serge Miguet

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Automatic detection of a falling person in video sequences has interesting applications in video -surveillance and is an important part of future pervasive home monitoring systems. In this paper, we propose a multiview approach to achieve this goal, where motion is modeled using a layered hidden Markov model (LHMM). The posture classification is performed(More)
License Plate Recognition (LPR) is mainly regarded as a solved problem. However, robust solutions able to face real-world scenarios still need to be proposed. Country-specific systems are mostly, designed, which can (artificially) reach high-level recognition rates. This option, however, strictly limits their applicability. In this paper, we propose an(More)
PURPOSE We propose to simulate an artificial four-dimensional (4-D) CT image of the thorax during breathing. It is performed by deformable registration of two CT scans acquired at inhale and exhale breath-hold. MATERIALS AND METHODS Breath-hold images were acquired with the ABC (Active Breathing Coordinator) system. Dense deformable registrations were(More)
Automatic detection of a falling person in video sequences is an important part of future pervasive home monitoring systems. We propose here a robust method to achieve this goal. Motion is modeled by a hierarchical hidden Markov model (HHMM) whose first layer states are related to the orientation of the tracked person. Finding a consistent way for robustly(More)
Moving objects extraction from image/video sequences is one of the most interesting, well-focused and well addressed but still challenging topic in computer vision. Results of segmentation depend on the variation of local or global light intensities, object’s shadow and background changes. Object recognition and tracking algorithms performance depend on(More)
In this article, we present a discrete definition of the classical visibility in computational geometry based on digital straight lines. We present efficient algorithms to compute the set of pixels in a non-convex domain that are visible from a source pixel. Based on these definitions, we define discrete geodesic paths in discrete domain with obstacles.(More)