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Person Re-Identification Based on Pose-Aware Segmentation

  • Wenfeng Zhang
  • Zhiqiang WeiEmail author
  • Lei Huang
  • Jie Nie
  • Lei Lv
  • Guanqun Wei
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11296)

Abstract

Person re-identification (Re-ID) is a key technology for intelligent video analysis. However, it is still a challenging task due to various complex background, different poses of person, etc. In this paper we try to address this issue by proposing a novel method based on person segmentation. Contrary to the previous method, we segment the person region from the image first. A pose-aware segmentation method (PA) is proposed by introducing the human pose into segmentation scheme. Then the deep learning features are extracted based on the person region instead of the whole bounding box. Finally, the person Re-ID results are acquired through the rank of Euclidean distance. Comprehensive experiments on two public person Re-ID datasets show the effectiveness of our method and the comparison experiments demonstrate that our method can outperform the state-of-the-art method.

Keywords

Person re-identification Complex background Person region Person segmentation Deep learning 

Notes

Acknowledgement

This work is supported by the National Natural Science Foundation of China (No. 61672475, No. 61402428, 61702471); Qingdao Science and Technology Development Plan (No. 16-5-1-13-jch).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Wenfeng Zhang
    • 1
  • Zhiqiang Wei
    • 1
    • 2
    Email author
  • Lei Huang
    • 1
    • 2
    • 4
  • Jie Nie
    • 1
  • Lei Lv
    • 3
    • 4
  • Guanqun Wei
    • 1
  1. 1.Ocean University of ChinaQingdaoChina
  2. 2.Qingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.School of Information Science and EngineeringShandong Normal UniversityJi’nanChina
  4. 4.Key Laboratory for Distributed Computer Software Novel TechnologyJi’nanChina

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