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Enhanced Active Color Image for Gait Recognition

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Biometric Recognition (CCBR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9967))

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Abstract

Active Energy Image (AEI) is an efficient template for gait recognition. However, the AEI is short of the temporal information. In this paper, we present a novel gait template, named Enhanced Active Color Image (EACI). The EACI is extract the difference of two interval in each gait frame, followed by calculating the width of that difference image and then mapping into RGB space with the ratio, describing the relative position, and composition them to a single EACI. To prove the validity of the EACI, we employ experiments on the USF HUMANID database. Experiment result shows that our EACI describes the dynamic, static and temporal information better. Compared with other published gait recognition approaches, we achieve competitive performance in gait recognition.

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Authors and Affiliations

  1. Xi’an Jiaotong University, Xi’an, 710049, Shaanxi, People’s Republic of China

    Yufei Shang, Yonghong Song & Yuanlin Zhang

Authors
  1. Yufei Shang
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  2. Yonghong Song
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  3. Yuanlin Zhang
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Corresponding author

Correspondence to Yonghong Song .

Editor information

Editors and Affiliations

  1. Sichuan University , Chengdu, China

    Zhisheng You

  2. Tsinghua University , Beijing, China

    Jie Zhou

  3. Beihang University , Beijing, China

    Yunhong Wang

  4. Chinese Academy of Sciences , Beijing, China

    Zhenan Sun

  5. Chinese Academy of Sciences , Beijing, China

    Shiguang Shan

  6. Sun Yat-sen University , Guangzhou, China

    Weishi Zheng

  7. Tsinghua University , Beijing, China

    Jianjiang Feng

  8. Sichuan University , Chengdu, China

    Qijun Zhao

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© 2016 Springer International Publishing AG

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Shang, Y., Song, Y., Zhang, Y. (2016). Enhanced Active Color Image for Gait Recognition. In: You, Z., et al. Biometric Recognition. CCBR 2016. Lecture Notes in Computer Science(), vol 9967. Springer, Cham. https://doi.org/10.1007/978-3-319-46654-5_51

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  • DOI: https://doi.org/10.1007/978-3-319-46654-5_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46653-8

  • Online ISBN: 978-3-319-46654-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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