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Leens+Jérôme+

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See detailReal-time processing of depth and color video streams to improve the reliability of depth maps
Pierard, Sébastien ULg; Leens, Jérôme ULg; Van Droogenbroeck, Marc ULg

Poster (2009, November)

Depth is a useful information in vision to understand the geometrical properties of an environment. Depth is traditionally computed in terms of a disparity map acquired by a stereoscopic system but, over ... [more ▼]

Depth is a useful information in vision to understand the geometrical properties of an environment. Depth is traditionally computed in terms of a disparity map acquired by a stereoscopic system but, over the last few years, several manufacturers have released single-lens cameras that directly capture depth information (also called range). This is an important technological breakthrough although range signals remain difficult to handle in practice, due to many reasons (low resolution, noise, low framerate, . . . ). Practitioners still struggle to use range data in their applications. The purpose of this paper is to give a brief introduction to range data (captured with a camera), discuss common limitations, and propose techniques to cope with difficulties typically encountered with range cameras. These techniques are based on a simultaneous view of the scene by a color and a depth camera that are combined to improve their interpretation in real time. [less ▲]

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See detailCombining Color, Depth, and Motion for Video Segmentation
Leens, Jérôme ULg; Pierard, Sébastien ULg; Barnich, Olivier et al

in Computer Vision Systems (2009)

This paper presents an innovative method to interpret the content of a video scene using a depth camera. Cameras that provide distance instead of color information are part of a promising young technology ... [more ▼]

This paper presents an innovative method to interpret the content of a video scene using a depth camera. Cameras that provide distance instead of color information are part of a promising young technology but they come with many diff culties: noisy signals, small resolution, and ambiguities, to cite a few. By taking advantage of the robustness to noise of a recent background subtraction algorithm, our method is able to extract useful information from the depth signals. We further enhance the robustness of the algorithm by combining this information with that of an RGB camera. In our experiments, we demonstrate this increased robustness and conclude by showing a practical example of an immersive application taking advantage of our algorithm. [less ▲]

Detailed reference viewed: 266 (34 ULg)