Bowen Cheng, Shuai Jiang, Yalong Pang, Shenshen Luan, Jing Lu
{"title":"Research on the Detection and Tracking of Moving Objects in Dynamic Scenes","authors":"Bowen Cheng, Shuai Jiang, Yalong Pang, Shenshen Luan, Jing Lu","doi":"10.1109/CCPQT56151.2022.00028","DOIUrl":null,"url":null,"abstract":"Aiming at the poor robustness of the moving objects detection and tracking algorithm in the dynamic scenes, a new moving objects tracking algorithm in the dynamic scenes is proposed, which combines the optical flow method and Kalman predictor, can solve the occlusion problem in target tracking. The optical flow method solves the detection of the moving objects problem, and the Kalman predictor is used to complete the moving target prediction and association. The experimental results show that, the proposed algorithm can work well in the stationary scenes and the dynamic scenes, and the accuracy of detection of moving objects in dynamic scenes is more effective than the optical flow method only.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCPQT56151.2022.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Aiming at the poor robustness of the moving objects detection and tracking algorithm in the dynamic scenes, a new moving objects tracking algorithm in the dynamic scenes is proposed, which combines the optical flow method and Kalman predictor, can solve the occlusion problem in target tracking. The optical flow method solves the detection of the moving objects problem, and the Kalman predictor is used to complete the moving target prediction and association. The experimental results show that, the proposed algorithm can work well in the stationary scenes and the dynamic scenes, and the accuracy of detection of moving objects in dynamic scenes is more effective than the optical flow method only.
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