Research Article
Video Shot Boundary Detection and Sports Video Classification Algorithm Based on Particle Filter
@ARTICLE{10.4108/eetsis.3955, author={Dongsheng Chen and Zhen Ni}, title={Video Shot Boundary Detection and Sports Video Classification Algorithm Based on Particle Filter}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={11}, number={3}, publisher={EAI}, journal_a={SIS}, year={2023}, month={10}, keywords={Deep learning, Particle filter, Sports video, Categorize, Edge detection, Key frame, Encoding mode}, doi={10.4108/eetsis.3955} }- Dongsheng Chen
Zhen Ni
Year: 2023
Video Shot Boundary Detection and Sports Video Classification Algorithm Based on Particle Filter
SIS
EAI
DOI: 10.4108/eetsis.3955
Abstract
INTRODUCTION: Sports video is a very important information resource. The classification of sports video with high accuracy can effectively improve the browsing and query effect of users. This project intends to study a motion video classification algorithm based on deep learning particle filter to solve the problems of strong subjectivity and low accuracy of existing motion video classification algorithms. A key box extraction method based on similarity is proposed. The moving video classification algorithm based on deep learning coding model is studied. Examples of various types of sports videos are analyzed. The overall performance of the motion video classification algorithm proposed in this paper is much better than other existing motion video classification algorithms. This algorithm can greatly improve the classification performance of motion video.
Copyright © 2023 D. Chen 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.
