Sports Video Augmented Reality Real-Time Image Analysis of Mobile Devices

Sports video is loved by the audience because of its unique charm, so it has high research value and application value to analyze and study the video data of competition. Based on the background of football match, this paper studies the football detection and tracking algorithm in football game video and analyzes the real-time image of real-time mobile devices in sports video augmented reality. Firstly, the image is preprocessed by image graying, image denoising, image binarization, and so on. Secondly, Hough transform is used to locate and detect football, and according to the characteristics of football, Hough transform is improved. Based on the good performance of SIFT algorithm in feature matching, a football tracking algorithm based on SIFT feature matching is proposed, which matches the detected football with the sample football. The simulation results show that the improved Hough transform can effectively detect football and has good antijamming performance. And the designed football tracking algorithm based on SIFT feature matching can accurately track the football trajectory; therefore, the football detection and tracking algorithm designed in this paper is suitable for real-time football monitoring and tracking.