DP-Pose: Multi-Person Pose Estimation in Video Sequence through Dynamic Programming
Deyuan Zhang, Junyuan Wang, Xiangbin Shi, Zhaokui Li, Fang Liu, Cuiwei Liu · 2019
Human pose estimation is an important research topic in the field of computer vision. Bottom-up methods such as OpenPose have become prevalent pose estimation methods because of its high efficiency and detection speed. But for poor quality video, the keypoints obtained by the bottom-up method have suffered from jitter and loss. In this paper, we propose DP-Pose, which constructs candidate pose sequence by selecting points in a region of the heatmap, improves constraint function by combining distance and confidence, and solves the optimal keypoints location by dynamic programming. The experimental results on class dataset show that DP-Pose can recover missing keypoint using heatmap data and obtain stable pose from candidate pose sequences.