3D silhouette tracking with occlusion inference

Wenkai Li; Hongxun Yao; Rongrong Ji; Tianqiang Liu; Debin Zhao

doi:10.1117/12.863525

4 August 2010 3D silhouette tracking with occlusion inference

Wenkai Li, Hongxun Yao, Rongrong Ji, Tianqiang Liu, Debin Zhao

Proceedings Volume 7744, Visual Communications and Image Processing 2010; 77442W (2010) https://doi.org/10.1117/12.863525
Event: Visual Communications and Image Processing 2010, 2010, Huangshan, China

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.

Citation Download Citation

Wenkai Li, Hongxun Yao, Rongrong Ji, Tianqiang Liu, and Debin Zhao "3D silhouette tracking with occlusion inference", Proc. SPIE 7744, Visual Communications and Image Processing 2010, 77442W (4 August 2010); https://doi.org/10.1117/12.863525

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KEYWORDS

Visualization

3D modeling

Visual process modeling

Particles

Optical tracking

Detection and tracking algorithms

3D acquisition

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