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Identifying People Using Body Sway in Case of Self-occlusion

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Frontiers of Computer Vision (IW-FCV 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1212))

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Abstract

We propose a method of identifying people in case of self-occlusion by using body sway measured at the head using a top-view camera. To accurately represent the identities of people as reflected in body sway, it is important to acquire accurate appearances in images. However, such images frequently contain defects, especially self-occlusion, that degrade the performance of one of the prevalent methods for identifying people because it uses whole-body regions to identify people. To solve the problem of self-occlusion in this context, our method computes silhouette images of regions at the head by applying a segmentation technique. To reflect people’s identities using body sway, we spatially divide the head region into local blocks and temporally measure movements in them. The results of experiments show that the proposed method can improve the performance of the prevalent method of identification from 17.3% to 57.9%.

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Acknowledgments

This work was partially supported by JSPS KAKENHI under grant number JP17K00238 and MIC SCOPE under grant number 172308003.

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Authors and Affiliations

  1. Tottori University, Tottori, 680-8550, Japan

    Takuya Kamitani, Yuta Yamaguchi, Masashi Nishiyama & Yoshio Iwai

Authors
  1. Takuya Kamitani
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  2. Yuta Yamaguchi
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  3. Masashi Nishiyama
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  4. Yoshio Iwai
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Corresponding author

Correspondence to Takuya Kamitani .

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Editors and Affiliations

  1. Saitama Institute of Technology, Saitama, Japan

    Wataru Ohyama

  2. Kyungpook National University, Daegu, Korea (Republic of)

    Soon Ki Jung

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Kamitani, T., Yamaguchi, Y., Nishiyama, M., Iwai, Y. (2020). Identifying People Using Body Sway in Case of Self-occlusion. In: Ohyama, W., Jung, S. (eds) Frontiers of Computer Vision. IW-FCV 2020. Communications in Computer and Information Science, vol 1212. Springer, Singapore. https://doi.org/10.1007/978-981-15-4818-5_11

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  • DOI: https://doi.org/10.1007/978-981-15-4818-5_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4817-8

  • Online ISBN: 978-981-15-4818-5

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