Application Research on Roller Skater Detection, Tracking, and Trajectory Prediction Based on Video Stream

Shaolou Duan,Lingfeng Meng,Delong Ma,Liangyu Mi,Bai Yuan Ding

doi:10.1155/2021/2702272

Abstract

With the continuous progress of science and technology, the sport of roller skating has developed rapidly and the technical level of the game has become higher and higher. Its sport performance has been rapidly improved. However, China’s roller skating is relatively late, and there is still a certain gap compared with many Western developed countries. In order to improve the performance of China’s roller skating, this study takes the representative Chinese and foreign excellent speed skaters as the research object and compares the sprinting technology of Chinese and foreign excellent speed skaters by using image measurement and image analysis to obtain the kinematic parameters and data of the athletes’ sprinting technology in the competition state. In view of the problem that the current video target tracking algorithm is easy to follow multiple targets, a video multiobject detection and tracking algorithm with improved tracking learning detection (TLD) is studied with the skater in the video as the research object. For the lost target, the prediction function of Kalman filter algorithm is used to track the trajectory of the typical target in the video, and the trajectory tracked by Kalman filter algorithm is used to compensate the lost part of TLD algorithm, so as to obtain the complete trajectory of the typical target in the video to improve the accuracy of video multiobject tracking. Since the existing trajectory prediction algorithms have the limitation of poor accuracy, a social-long short-term memory (Social-LSTM) network-based video typical target trajectory prediction algorithm is proposed to predict the trajectory sequences of typical targets to be detected by incorporating the contextual environment information and the interaction relationship between multiple target trajectories into the Social-LSTM network. The simulation results show that the proposed trajectory prediction algorithm outperforms the traditional LSTM algorithm, Hidden Markov Model Algorithm, and Hybrid Gaussian model algorithm, which is helpful to improve the accuracy of video roller skater target trajectory prediction, and the tracking success rate is 0.98.

Highlights

With the continuous development and growth of sports, roller skating has been flourishing, and the new projects of modern roller skating have emerged and diversified, developing different forms of sports such as speed skating, roller skating ball, extreme roller skating, and figure skating, which are popular among people [1]. e International Roller Derby Federation was officially admitted as a member of the International Olympic Committee (IOC) at the IOC Session held in Prague, Czechoslovakia, in 2007 [2]
We propose a video multiobject detection and tracking algorithm based on improved tracking learning detection (TLD) to obtain the complete trajectories of moving targets. e moving trajectory data are analyzed, and a Social-LSTM-based video typical target prediction algorithm is proposed to improve the accuracy of prediction by combining contextual feature information
In order to improve the accuracy of video target tracking, this paper proposes a video multiobject trajectory acquisition algorithm with improved TLD to track and obtain the running behavior trajectory of the target in the case of target movement. e TLD algorithm is used as the basic tracking algorithm, and the Kalman filtering algorithm is used as the auxiliary tracking algorithm. e trajectory obtained by the Kalman filtering algorithm is used to supplement the missing part of the trajectory obtained by the TLD algorithm, and the complete trajectory of the video target is obtained. e specific steps of the algorithm are as follows: Step 1: video is input

Summary

Introduction

“Roller skating is called roller skating; it is an ice sport in the land auxiliary training process gradually evolved in the formation of sport.” With the continuous development and growth of sports, roller skating has been flourishing, and the new projects of modern roller skating have emerged and diversified, developing different forms of sports such as speed skating, roller skating ball, extreme roller skating, and figure skating, which are popular among people [1]. e International Roller Derby Federation was officially admitted as a member of the International Olympic Committee (IOC) at the IOC Session held in Prague, Czechoslovakia, in 2007 [2]. Erefore, it is very meaningful to study the short-distance project of speed skating in China, which can, on the one hand, provide certain training theoretical reference for China’s speed skating coaches, so as to improve the technical level of China’s speed skaters in the short-distance project and improve the sports performance, on the other hand, provide help for the popularization of China’s speed skating technology, and can promote the further development of China’s speed skating sport It can promote the further development of speed skating in China and play an indirect role in the implementation of the latest national fitness program in China [7, 8]. It has a very important role in the generation of initial speed, so the study of sprinting technology is very important [11]. e technical movements in the sprinting process are very complicated, and the details of each technical movement are changed in the short-sprinting stage, such as body posture, pedal angle, stride frequency, stride length, and joint angle. ese elements are the key to the sprinting technique, and the changes of these elements will directly affect the athletic level of the runner, and they interact with each other and are interrelated, the chain reaction of several factors

Related Work

Data Preprocessing

Roller Derby Forecast

Method

Findings

Conclusions