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

被引：0
|
作者：
Kurosaki, Tomoyuki [1 ]
Tan, Joo Kooi [2 ]
机构：
[1] Kyushu Inst Technol, Grad Sch Engn, Tobata Ku, 1-1 Sensui Cho, Kitakyushu, Fukuoka 8048550, Japan
[2] Kyushu Inst Technol, Fac Engn, Tobata Ku, 1-1 Sensui Cho, Kitakyushu, Fukuoka 8048550, Japan
来源：
PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB2020) | 2020年
关键词：
Posture; Posture analysis; Pedestrian; MY VISION; Deep learning; DeMoN;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：485 / 489
页数：5
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