Flexible Top-view Human Pose Estimation for Detection System Via CNN

被引:0
|
作者
Go, Ryuji [1 ]
Aoki, Yoshimitsu [2 ]
机构
[1] Keio Univ, Grad Sch Sci & Technol, Kohoku Ku, 3-14-1 Hiyoshi, Yokohama, Kanagawa 2238522, Japan
[2] Keio Univ, Dept Elect & Elect Engn, Kohoku Ku, 3-14-1 Hiyoshi, Yokohama, Kanagawa 2238522, Japan
关键词
Pose Estimation; Convolutional Neural Networks; Top-view;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We propose the DeepPose-based pose estimation system that is flexible with the change of bounding-box range for top-view images. Our purpose is to link person detection system and pose estimation system. We introduce Bounding-box Curriculum Learning (BCL) and Recurrent Pose Estimation (RPE). BCL is a learning technique of CNN inspired from Curriculum Learning. RPE is a recurrent process of pose estimation that fixes the bounding-box range in response to the estimated results. We show the effect of proposed methods compared to normal learned CNN-based pose estimator on our original top-view dataset.
引用
收藏
页数:4
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