3D occlusion recovery using few cameras

13 years 3 months ago
3D occlusion recovery using few cameras
We present a practical framework for detecting and modeling 3D static occlusions for wide-baseline, multi-camera scenarios where the number of cameras is small. The framework consists of an iterative learning procedure where at each frame the occlusion model is used to solve the voxel occupancy problem, and this solution is then used to update the occlusion model. Along with this iterative procedure, there are two contributions of the proposed work: (1) a novel energy function (which can be minimized via graph cuts) specifically designed for use in this procedure, and (2) an application that incorporates our probabilistic occlusion model into a 3D tracking system. Both qualitative and quantitative results of the proposed algorithm and its incorporation with a 3D tracker are presented for support.
Mark A. Keck, James W. Davis
Added 12 Oct 2009
Updated 28 Oct 2009
Type Conference
Year 2008
Where CVPR
Authors Mark A. Keck, James W. Davis
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