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Spatial Constrained Fine-Grained Color Name for Person Re-identification

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MultiMedia Modeling (MMM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9516))

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Abstract

Person re-identification is a key technique to match different persons observed in non-overlapping camera views. It’s a challenging problem due to the huge intra-class variations caused by illumination, poses, viewpoints, occlusions and so on. To address these issues, researchers have proposed many visual descriptors. However, these visual features may be unstable in complicated environment. Comparatively, the semantic features can be a good supplement to visual feature descriptors for its robustness. As a kind of representative semantic features, color name is utilized in this paper. The color name is a semantic description of an image and shows good robustness to photometric variations. Traditional color name based methods are limited in discriminative power due to the finite color categories, only 11 or 16 kinds. In this paper, a new fine-grained color name approach based on bag-of-words model is proposed. Moreover, spatial information, with its advantage in strengthening constraints among features in variant environment, is further applied to optimize our method. Extensive experiments conducted on benchmark datasets have shown great superiorities of the proposed method.

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Acknowledgement

The research was supported by National Nature Science Foundation of China (61303114, 61231015, 61170023), the Specialized Research Fund for the Doctoral Program of Higher Education (20130141120024), the Technology Research Project of Ministry of Public Security (2014JSYJA016), the China Postdoctoral Science Foundation funded project (2013M530350), the major Science and Technology Innovation Plan of Hubei Province (2013AAA020), the Guangdong-Hongkong Key Domain Break-through Project of China (2012A090200007), and the Special Project on the Integration of Industry, Education and Research of Guangdong Province (2011B090400601). Nature Science Foundation of Hubei Province (2014CFB712). Jiangxi Youth Science Foundation of China (20151BAB217013).

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Authors and Affiliations

  1. National Engineering Research Center for Multimedia Software, School of Computer, Wuhan University, Wuhan, 430072, China

    Yang Yang, Yuhong Yang, Mang Ye, Wenxin Huang, Zheng Wang, Chao Liang & Lei Yao

  2. Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China

    Yuhong Yang & Chao Liang

  3. University of Chinese Academy of Sciences, Beijing, China

    Chunjie Zhang

Authors
  1. Yang Yang
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  2. Yuhong Yang
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  3. Mang Ye
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  4. Wenxin Huang
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  5. Zheng Wang
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  6. Chao Liang
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  7. Lei Yao
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  8. Chunjie Zhang
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Corresponding author

Correspondence to Yuhong Yang .

Editor information

Editors and Affiliations

  1. University of Texas at San Antonio, San Antonio, USA

    Qi Tian

  2. Dept. of Information Engineering, University of Trento, Povo, Trento, Italy

    Nicu Sebe

  3. EECS, University of Central Florida, Orlando, Florida, USA

    Guo-Jun Qi

  4. EURECOM, Sophia-Antipolis, France

    Benoit Huet

  5. Hefei University of Technology, Hefei, Anhui, China

    Richang Hong

  6. School of Computing and Information, Hefei University of Technology, Hefei, Anhui, China

    Xueliang Liu

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Yang, Y. et al. (2016). Spatial Constrained Fine-Grained Color Name for Person Re-identification. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9516. Springer, Cham. https://doi.org/10.1007/978-3-319-27671-7_74

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  • DOI: https://doi.org/10.1007/978-3-319-27671-7_74

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27670-0

  • Online ISBN: 978-3-319-27671-7

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