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

页码：485 / 489

页数：5

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