Sports Video Object Tracking Algorithm Based on Optimized Particle Filter

Qingbao Wang; Chenbo Zhao

doi:10.4108/eetsis.3935

Authors

Qingbao Wang BaiCheng Normal University
Chenbo Zhao Jiamusi University

DOI:

https://doi.org/10.4108/eetsis.3935

Keywords:

Moving target detection, Gaussian mixture model, Particle filter, RGB color columnar structure

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.

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