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Published in:
2013 | OriginalPaper | Chapter
Person Re-identification by Local Feature Based on Super Pixel
Authors : Cheng Liu, Zhicheng Zhao
Published in: Advances in Multimedia Modeling
Publisher: Springer Berlin Heidelberg
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In many multi-camera surveillance systems, there is a need to identify whether a captured person have emerged before over the network of cameras. This is the person re-identification problem. In this paper, we propose a novel re-identification method based on super pixel feature. Firstly, local C-SIFT features based on super pixel are extracted as visual words, and appearance details are used to describe detecting objects. Secondly, a TF-IDF vocabulary index tree is built to speed up person search. Finally, an image-retrieval way is adopted to implement person re-identification. Experimental results on ETHZ dataset show that our method is better than the approach proposed by Schwartz et.al and two machine learning methods based on SVM and PCA.