Keyframe extraction for human motion capture data based on affinity propagation

Abstract

Keyframe extraction is important for video retrieval. In order to realize frequency adaptive human motion sequence resampling and achieve high quality keyframe, we propose a new keyframe extraction method for human motion sequence. First, we define the inter-frame similarity metric based on the features of human body parts. Then, the keyframe extraction is realized by the affine propagation clustering algorithm. The proposed method starts from the information distribution of the video itself, adaptively searches for the optimal keyframe of the video, and the operation speed is fast. Finally, the evaluation of the sequence reconstruction based on keyframe is verified. A comparative experiment conducted on the CMU database verified the efficiency of our method.