Design of Target Detection and Tracking System for Sports Video

Abstract

Video motion target tracking has been widely used in the field of sports. Content-based video search has a broad application prospect and attracts more and more researchers' attention. In view of the shortcomings of moving object detection in motion video at present, a human motion recognition method based on correlation vector machine is proposed. Combined with the improved Gaussian mixture model of moving object detection and tracking method in motion video, moving object detection and tracking are carried out. The design of the system is realized. Firstly, it collects sports videos, considers all kinds of sports objects in sports videos, uses improved background update difference method to detect sports objects, then uses correlation vector machine to recognize human motion, and finally uses AdaBoost classifier to use it in multiple sports videos and sports objects. Carry out follow-up experiments. Results in this way, we can track the sports target in sports video accurately and quickly, and the real-time performance of sports target tracking is better than other tracking methods, which provides a new research tool for tracking sports target in sports video.