Contour Packing for Shape Recognition
讲座名称：
Contour Packing for Shape Recognition
讲座时间：
2009-06-29
讲座人：
施建博
形式：
校区：
兴庆校区
实践学分：
讲座内容：
We introduce a method for 'packing' salient but fragmented image contours/segments into recognizable object shapes. This method requires few training examples, and is resistant to image clutter.
In total, our method addresses three challenges: 1) object shape variation, 2) learning a discriminative score function for detection, and 3) unpredictable fragmentation of segments or contours. Previous works have addressed either both object shape variation and discriminative training, or both unpredictable fragmentation and object shape variation, but not all three.
Our approach uses salient contours as integral tokens for shape matching. We seek a maximal, holistic matching of shapes. Shape features are extracted from large spatial extent, together with long-range contextual relationships among object parts. Our approach allow imperfect image segments to be `glued', to achieve one(object)-to-many(segments), or many(object parts)-to-many(segments) matching. We demonstrate that many-to-many shape matching can be trained discriminatively, using simple bounding box around objects as feedback. (This is joint work with Qihui Zhu, Praveen Srinivasan, Liming Wang, and Yang Wu.)
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