Estimation of Self-Posture of a Pedestrian Using MY VISION and Deep Learning
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- Kurosaki Tomoyuki
- Graduate school of Engineering, Kyushu Institute of Technology
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- Tan Joo Kooi
- Faculty of Engineering, Kyushu Institute of Technology
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
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- 人工生命とロボットに関する国際会議予稿集
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人工生命とロボットに関する国際会議予稿集 25 485-489, 2020-01-13
株式会社ALife Robotics
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詳細情報 詳細情報について
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- CRID
- 1390846609806614528
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- ISSN
- 21887829
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- OpenAIRE
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- 抄録ライセンスフラグ
- 使用不可