Application of human motion recognition technology in extreme learning machine

International Journal of Advanced Robotic Systems

article

Anzhu Miao¹  Feiping Liu² 

[1] Sports Department, Guizhou University of Finance and Economics;PE Department, Wuhan Institute of Technology

关键词: Human motion recognition;    extreme learning machine;    feature extraction;    classifier;   

DOI  :  10.1177/1729881420983219

学科分类：社会科学、人文和艺术（综合）

来源: InTech

【 摘 要 】

Human motion recognition is a branch of computer vision research and is widely used in fields like interactive entertainment. Most research work focuses on human motion recognition methods based on traditional video streams. Traditional RGB video contains rich colors, edges, and other information, but due to complex background, variable illumination, occlusion, viewing angle changes, and other factors, the accuracy of motion recognition algorithms is not high. For the problems, this article puts forward human motion recognition based on extreme learning machine (ELM). ELM uses the randomly calculated implicit network layer parameters for network training, which greatly reduces the time spent on network training and reduces computational complexity. In this article, the interframe difference method is used to detect the motion region, and then, the HOG3D feature descriptor is used for feature extraction. Finally, ELM is used for classification and recognition. The results imply that the method proposed here has achieved good results in human motion recognition.

【 授权许可】

CC BY