A target tracking system based on multi-camera information fusion

Minxuan Cao, Zhihao Sun, Geng Han, Fang Deng*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In order to promote the development of the public security sky-eyes system and the Internet of things, our system completes the integrated multi-camera cooperative tracking of multi-targets. The system uses the self-calibration method to map the camera detection results to the global coordinates through perspective transformation. The system uses YOLO-X network for target recognition and classification; The improved SORT algorithm is used to track and improve the ID switch problem. At the same time, 3D-box method is used to regress the attitude angle information of the object, so as to judge the state of the object and correct the deviation. On the premise of ensuring stability, the system achieves a faster running speed. It uses an RTX3080 GPU to accelerate, the overall speed reaches 60Hz, the classification accuracy is close to 100%, and stable target tracking is achieved. The system algorithm fully considers the occlusion, the change of target feature state, the disappearance of the target, etc., and can still ensure good results.

Original languageEnglish
Title of host publicationProceedings - 2022 Chinese Automation Congress, CAC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4225-4229
Number of pages5
ISBN (Electronic)9781665465335
DOIs
Publication statusPublished - 2022
Event2022 Chinese Automation Congress, CAC 2022 - Xiamen, China
Duration: 25 Nov 202227 Nov 2022

Publication series

NameProceedings - 2022 Chinese Automation Congress, CAC 2022
Volume2022-January

Conference

Conference2022 Chinese Automation Congress, CAC 2022
Country/TerritoryChina
CityXiamen
Period25/11/2227/11/22

Keywords

  • Attitude angle regression
  • Information fusion
  • Multi-target tracking

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