Volume 9 Issue 5
Sep.  2016
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WANG Li. Pedestrian re-identification based on fusing low-level and mid-level features[J]. Chinese Optics, 2016, 9(5): 540-546. doi: 10.3788/CO.20160905.0540
Citation: WANG Li. Pedestrian re-identification based on fusing low-level and mid-level features[J]. Chinese Optics, 2016, 9(5): 540-546. doi: 10.3788/CO.20160905.0540

Pedestrian re-identification based on fusing low-level and mid-level features

doi: 10.3788/CO.20160905.0540
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  • Corresponding author: E-mail:44417020@qq.com
  • Received Date: 05 Apr 2016
  • Rev Recd Date: 26 May 2016
  • Publish Date: 01 Oct 2016
  • Aiming at the problem of low recognition rate in the existing pedestrian re-identification algorithm using single low-level feature, a new method by fusing low-level and mid-level features is proposed, which identifies person in a coarse to fine strategy. First, the pedestrian is recognized roughly by color and texture features. Then, the human body is divided into three parts, including head, main body and leg. Head is ignored for its few useful information. A mid-level dictionary method is proposed and the dictionary is trained using patches from main body and leg, and then mid-level feature is computed for fine recognition. Fusing mid-level and low-level features can be not only discriminative but also representative. The experimental results indicate that the proposed method can increase nAUC by 6.3% compared with the existing methods, which is more robust to occlusion and background adhesion.

     

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