Human movement summarization and depiction from videos
Yijuan Lu, Hao Jiang · 2013
Human movement summarization and depiction from videos is to automatically turn an input video into high level action illustrations, in which the movements of the body parts are visualized using arrows and motion particles. Motion depiction compactly illustrates how specific movements are performed. Previous action summarization methods reply on 3D motion capture or manually labeled data, without which depicting actions is a challenging task. In this paper, we propose a novel scheme to automatically summarize and depict human movements from 2D videos without 3D motion capture or manually labeled data. The proposed method first segments videos into sub-actions with an effective streamline matching scheme. Then, to estimate human movement, we propose a novel trajectory following method to track points by using both body part detection and optical flow. With the estimated movement, we depict the human articulated motion with arrows and motion particles. Our experiments on a variety of videos show that the proposed method is effective in summarizing complex human movements and generating compact depictions.