3D Human Motion Key-frames Extraction Based on Asynchronous Learning Factor PSO

摘要：

　　Key-frames extraction technology for motion capture data can extract some important frames which describe the original motion sequence well, it is useful in motion retrieval, compression and edition. In this paper, we propose a new method for extracting key frames from motion capture sequence based on asynchronous learning factor PSO (Particle Swarm Optimization). Our proposed approach consists of three steps. Firstly, we initialize every particle which represents a series of key-frames. Secondly, the algorithm searches the global optimal value through asynchronous learning factor. Finally, we get the best key-frames set based on fitness function which is calculated by compression ratio and reconstruction error rate. Experiment results show that our method extracts key-frames efficiently which can describe the original motion sequence well.

关键词： key-frames extraction motion sequence PSO learning factor

作者: Yi Zhang Jinchuan Cao

作者单位: Information Engineering College University of Dalian Dalian,China

会议类型: 国际会议

会议名称: 2015 Fifth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2015)(第五届仪器测量、计算机通信与控制国际会议)

会议地点: 秦皇岛

会议语种:英文

页码: 1617-1620

在线出版日期: 2015-09-18（万方平台首次上网日期，不代表论文的发表时间）