Gait Recognition using Identity-Aware Adversarial Data Augmentation

Koki Yoshino, Kazuto Nakashima, Jeongho Ahn, Yumi Iwashita, Ryo Kurazume

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

抄録

Gait recognition is a non-contact person identification method that utilizes cameras installed at a distance. However, gait images contain person-agnostic elements (covariates) such as clothing, and the removal of covariates is important for identification with high performance. Disentanglement representation learning, which separates gait-dependent information such as posture from covariates by unsupervised learning, has been attracting attention as a method to remove covariates. However, because the amount of gait data is negligible compared to other computer vision tasks, such as image recognition, the separation performance of existing methods is insufficient. In this study, we propose a gait recognition method to improve the separation performance, which augments the training data by adversarial generation based on identity features, separated by disentanglement representation learning. The proposed method first separates gait-dependent features (pose features) and appearance-related covariate features (style features) from gait videos based on disentanglement representation learning. Then, synthesized gait images are generated by exchanging pose features between gait images of the person under different walking conditions, followed by adding them to the training data. The experiments indicate that our method can improve the separation performance, and generate high-quality gait images that are effective for data augmentation.

本文言語英語
ホスト出版物のタイトル2022 IEEE/SICE International Symposium on System Integration, SII 2022
出版社Institute of Electrical and Electronics Engineers Inc.
ページ596-601
ページ数6
ISBN(電子版)9781665445405
DOI
出版ステータス出版済み - 2022
イベント2022 IEEE/SICE International Symposium on System Integration, SII 2022 - Virtual, Narvik, ノルウェー
継続期間: 1月 9 20221月 12 2022

出版物シリーズ

名前2022 IEEE/SICE International Symposium on System Integration, SII 2022

会議

会議2022 IEEE/SICE International Symposium on System Integration, SII 2022
国/地域ノルウェー
CityVirtual, Narvik
Period1/9/221/12/22

!!!All Science Journal Classification (ASJC) codes

  • 人工知能
  • ハードウェアとアーキテクチャ
  • 生体医工学
  • 制御およびシステム工学
  • 機械工学
  • 制御と最適化

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