Research and Implementation of Sports Entity Simulation Based on Heterogeneous Binocular Vision

Abstract

To study the value of heterogeneous binocular vision in the detection of sports targets, a Zynq-based joint software and hardware design method is proposed, and a mobile object detection system for binocular vision is developed based on it. This paper introduces the relevant technologies and theories used in the system design. First, the basic principles and various modules of the binocular stereo vision process are introduced, including camera tuning, stereo correction, stereo tuning, and telescope stereo vision. Based on the depth information, a method to detect and measure motor targets was developed. Finally, combined with the improved mobile target detection algorithm, the real-time methodology research and algorithm design to determine the target range are completed. The performance of the moving target detection system based on binocular stereo vision and the moving target detection and ranging algorithm are tested and analyzed. We know that the front and rear width of the moving target (the person tested in this paper) is at least 10 cm, while the error value of the ranging algorithm in this paper is within 6 meters, and the average error is less than 10 cm. According to the characteristics of binocular stereo vision, the farther the viewing angle is, the smaller the parallax value of the left and right image pixels will be. Therefore, the insignificant change of depth information will bring some errors to the ranging algorithm. The greater the measurement error is, the lower the percentage deviation of the measurement result is within 2%. It also shows that the target ranging algorithm in this paper can ensure good accuracy within a certain distance. Through this method, we can obtain the accurate data of moving objects in sports competition, so as to improve the training method of athletes and improve the competition results.