Motion recognition technology of badminton players in sports video images

Abstract

Intelligent identification technology has made great progress in transportation, and its application in sports has attracted widespread attention. This research mainly discusses the research of human motion recognition technology in sports dance video images. In geometric algebraic space, using instance templates, a new cfrdF method, using css-based similarity of human body features as features, to construct an angle-adaptive and continuous-scale space template matching algorithm to calculate the similarity between horizontal plates and detected images value, set a certain threshold, so as to match the area where the human body is located. Based on the actual video analysis and display, using the self-similar structure of the color of the human object as the basic feature, it is described by the geometric algebra method, and the human body in the video image is extracted using template convolution objects and design adaptive template functions to extract human movements from sports dance video images. By loading each test video in turn, the posture of the characters in the video is checked every 30 s, and the approximate positions of the head and feet are marked and output to a txt file. Because lying on the ground during sports dance is a way of matching by height correction, the accuracy is less disturbed, but it can still reach 90.9%. The research results show that the template matching robot model proposed in this paper can accurately and robustly extract human objects in video.