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Attribute Discovery for Person Re-Identification

  • Takayuki Umeda
  • Yongqing Sun
  • Go Irie
  • Kyoko Sudo
  • Tetsuya Kinebuchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9517)

Abstract

An incremental attribute discovery method for person re-identification is proposed in this paper. Recent studies have shown the effectiveness of the attribute-based approach. Unfortunately, the approach has difficulty in discriminating people who are similar in terms of the pre-defined semantic attributes. To solve this problem, we automatically discover and learn new attributes that permit successful discrimination through a pair-wise learning process. We evaluate our method on two benchmark datasets and demonstrate that it significantly improves the performance of the person re-identification task.

Keywords

Person re-identification Attribute discovery Incremental leaning 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Takayuki Umeda
    • 1
  • Yongqing Sun
    • 1
  • Go Irie
    • 1
  • Kyoko Sudo
    • 1
  • Tetsuya Kinebuchi
    • 1
  1. 1.NTTYokosukaJapan

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