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Salient Color Names for Person Re-identification

  • Yang Yang
  • Jimei Yang
  • Junjie Yan
  • Shengcai Liao
  • Dong Yi
  • Stan Z. Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8689)

Abstract

Color naming, which relates colors with color names, can help people with a semantic analysis of images in many computer vision applications. In this paper, we propose a novel salient color names based color descriptor (SCNCD) to describe colors. SCNCD utilizes salient color names to guarantee that a higher probability will be assigned to the color name which is nearer to the color. Based on SCNCD, color distributions over color names in different color spaces are then obtained and fused to generate a feature representation. Moreover, the effect of background information is employed and analyzed for person re-identification. With a simple metric learning method, the proposed approach outperforms the state-of-the-art performance (without user’s feedback optimization) on two challenging datasets (VIPeR and PRID 450S). More importantly, the proposed feature can be obtained very fast if we compute SCNCD of each color in advance.

Keywords

Salient color names color descriptor feature representation person re-identification 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Yang Yang
    • 1
  • Jimei Yang
    • 2
  • Junjie Yan
    • 1
  • Shengcai Liao
    • 1
  • Dong Yi
    • 1
  • Stan Z. Li
    • 1
  1. 1.Center for Biometrics and Security Research & National Laboratory of Pattern RecognitionInstitute of Automation, Chinese Academy of SciencesChina
  2. 2.University of CaliforniaMercedUSA

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