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2007
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Inferring 3D Volumetric Shape of Both Moving Objects and Static Background Observed by a Moving Camera

9 years 6 months ago
Inferring 3D Volumetric Shape of Both Moving Objects and Static Background Observed by a Moving Camera
We present a novel approach to inferring 3D volumetric shape of both moving objects and static background from video sequences shot by a moving camera, with the assumption that the objects move rigidly on a ground plane. The 3D scene is divided into a set of volume elements, termed as voxels, organized in an adaptive octree structure. Each voxel is assigned a label at each time instant, either as empty, or belonging to background structure, or a moving object. The task of shape inference is then formulated as assigning each voxel a dynamic label which minimizes photo and motion variance between voxels and the original sequence. We propose a three-step voxel labeling method based on a robust photo-motion variance measure. First, a sparse set of surface points are utilized to initialize a subset of voxels. Then, a deterministic voxel coloring scheme carves away the voxels with large variance. Finally, the labeling results are refined by a Graph Cuts based optimization method to enforce ...
Chang Yuan, Gérard G. Medioni
Added 14 Aug 2010
Updated 14 Aug 2010
Type Conference
Year 2007
Where CVPR
Authors Chang Yuan, Gérard G. Medioni
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