Research Article
Sports Video Object Tracking Algorithm Based on Optimized Particle Filter
@ARTICLE{10.4108/eetsis.3935, author={Qingbao Wang and Chenbo Zhao}, title={Sports Video Object Tracking Algorithm Based on Optimized Particle Filter}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={11}, number={3}, publisher={EAI}, journal_a={SIS}, year={2023}, month={10}, keywords={Moving target detection, Gaussian mixture model, Particle filter, RGB color columnar structure}, doi={10.4108/eetsis.3935} }- Qingbao Wang
Chenbo Zhao
Year: 2023
Sports Video Object Tracking Algorithm Based on Optimized Particle Filter
SIS
EAI
DOI: 10.4108/eetsis.3935
Abstract
INTRODUCTION: Particle filter based human motion video target tracking technology has become a trend. This project intends to apply particle filters to image processing of human activities. Firstly, an improved particle filter model is used to track moving video objects. The purpose is to further improve the tracking effect and increase the tracking accuracy. HSV distribution model was used to establish target observation model. The algorithm is combined with the weight reduction algorithm to realize the human motion trajectory detection in the target observation mode. The model was then confirmed by an examination of sports player videos. Experiments show that this method can be used to track people in moving images of sports. Compared with other methods, this method has higher computational accuracy and speed.
Copyright © 2023 Q. Wang et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
