Fall Recognition Approach Based on Human Skeleton Information

摘要：

　　In this paper,we present a fast approach for fall recognition.This approach according to human-body skeleton information which was obtained from Kinect sensor.First,following the falls defined by FICSIT,head and center joints,and their relative distance are considered as feature to describe the behavior.Second,applying the slide-window method and threshold for behavior action stage,motion feature vector was extracted.In the end,falls were trained and recognized by Optimal Levenberg-Marquardt BP classification algorithm.Experimental results show that the approach is high-efficiency,and rate of accuracy reaches 90%.

关键词： component behavior recognition fall recognition Kinect skeleton information

作者: LUO Kai JIN Xiao-feng

作者单位: Intelligent Information Processing Lab., Dept. of Computer Science & Technology Yanbian University Yanji, China

会议类型: 国际会议

会议名称: 2016 Sixth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2016)(第六届仪器测量、计算机通信与控制国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 707-711

在线出版日期: 2016-07-21（万方平台首次上网日期，不代表论文的发表时间）