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Proceedings Paper

3D silhouette tracking with occlusion inference
Author(s): Wenkai Li; Hongxun Yao; Rongrong Ji; Tianqiang Liu; Debin Zhao
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Paper Abstract

It is a challenging problem to robustly track moving objects from image sequences because of occlusions. Previous methods did not exploit depth information sufficiently. Based on multiple camera scenes, we propose a 3D silhouette tracking framework to resolve occlusions and recover the appearances in 3D space, which enhances tracking effectiveness. In the framework, 2D object silhouettes are initially gained by Snake. Then a Voxel Space Carving procedure is introduced to simultaneously generate the occlusion model and visual hull of objects. Next, we adopt Particle Filter to select the valuable parts of occlusion model and combine them with the initial object silhouettes to generate the updated visual hull. Finally, updated visual hull of the objects are re-projected to each view to obtain their final contours. The experiments under the public LAB and SCULPTURE datasets validate the feasibility and effectiveness of our framework.

Paper Details

Date Published: 4 August 2010
PDF: 9 pages
Proc. SPIE 7744, Visual Communications and Image Processing 2010, 77442W (4 August 2010); doi: 10.1117/12.863525
Show Author Affiliations
Wenkai Li, Harbin Institute of Technology (China)
Hongxun Yao, Harbin Institute of Technology (China)
Rongrong Ji, Harbin Institute of Technology (China)
Tianqiang Liu, Harbin Institute of Technology (China)
Debin Zhao, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 7744:
Visual Communications and Image Processing 2010
Pascal Frossard; Houqiang Li; Feng Wu; Bernd Girod; Shipeng Li; Guo Wei, Editor(s)

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