Estimation of Self-Posture of a Pedestrian Using MY VISION and Deep Learning

DOI オープンアクセス

説明

A system is proposed that performs gait analysis of a pedestrian to prevent fall. In the system, a user walks with a chest-mounted camera. His/her walking posture is estimated using a pair of images obtained from the camera. Normally it is difficult to estimate the camera movement, when the parallax of the image pair is small. Therefore, the system uses a convolutional neural network. Optical flow and camera movement, and depth images are estimated alternately. Satisfactory results were obtained experimentally.

収録刊行物

詳細情報 詳細情報について

  • CRID
    1390846609806614528
  • DOI
    10.5954/icarob.2020.gs1-2
  • ISSN
    21887829
  • 本文言語コード
    en
  • データソース種別
    • JaLC
    • Crossref
    • OpenAIRE
  • 抄録ライセンスフラグ
    使用不可

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