Shape Constrained Figure-Ground Segmentation and Tracking

14 years 11 months ago
Shape Constrained Figure-Ground Segmentation and Tracking
Global shape information is an effective top-down complement to bottom-up figure-ground segmentation as well as a useful constraint to avoid drift during adaptive tracking. We propose a novel method to embed global shape information into local graph links in a Conditional Random Field (CRF) framework. Given object shapes from several key frames, we automatically collect a shape dataset onthe- fly and perform statistical analysis to build a collection of deformable shape templates representing global object shape. In new frames, simulated annealing and local voting align the deformable template with the image to yield a global shape probability map. The global shape probability is combined with a region-based probability of object boundary map and the pixel-level intensity gradient to determine each link cost in the graph. The CRF energy is minimized by min-cut, followed by Random Walk on the uncertain boundary region to get a soft segmentation result. Experiments on bo...
Zhaozheng Yin, Robert T. Collins
Added 15 May 2009
Updated 30 Dec 2010
Type Conference
Year 2009
Where CVPR
Authors Zhaozheng Yin, Robert T. Collins
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