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Implicit Sparse Shape Representation: A Unified Framework for Object Segmentation and Recognition

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2 Author(s)
J. Yao ; J. Yao is with the Laboratory of State Key Discipline of Communication and Information System, Department of Information Science and Electronic Engineering, Zhejiang University, Hang Zhou, CO 310027 China.( ; H. Yu

Given a classified probabilistic shape dictionary, and an image with a shape similar to some of the elements in the dictionary, this letter introduces a sparse representation based framework with a twofold goal. First, to select a sparse shape combination from the dictionary that best represents the shape, and second, to accurately segment the image taking into account both the sparse shape combination and the image information. A new energy function that combines the region-based segmentation with sparse representation is introduced to accomplish both goals simultaneously. The experimental results show the superior segmentation and recognition capabilities of the proposed model.

Published in:

IEEE Signal Processing Letters  (Volume:PP ,  Issue: 99 )