Key Pose Frame Extraction Method of Human Motion Based on 3D Framework and X-Means

The key pose frames of a human motion pose sequence, play an important role in the compression, retrieval and semantic analysis of continuous human motion. The current available clustering methods in literatures are difficult to determine the number of key pose frames automatically, and may destroy the postures' temporal relationships while extracting key frames. To deal with this problem, this paper proposes a new key pose frames extraction method on the basis of 3D space distances of joint points and the improved X-means clustering algorithm. According to the proposed extraction method, the final key pose frame sequence could be obtained by describing the posture of human body with space distance of particular joint points and then the time-constraint X-mean algorithm is applied to cluster and filtrate the posture sequence. The experimental results show that the proposed method can automatically determine the number of key frames and save the temporal characteristics of motion frames according to the motion pose sequence.