Multi-Object Tracking Method for Aerial Images Based on ReID-Byte

Bo Wang, Yongmei Cheng, Qiang Wang, Peng He, Xiao Yang, Xinhua Lei

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

Abstract

Aiming at the problems of ID Switch and track fragment caused by the ground target occlusion in aerial video tracking, a multi-object tracking(MOT) method based on ReID-Byte is proposed. This method introduces the ReID model on the basis of the Byte algorithm to extract the appearance feature of the targets. This paper uses the multi-task learning method to train the YOLOX detector and the ReID model, and the detection confidence is used as the measure to separate the detection results to the high-scoring boxes and the low-scoring boxes for inter-frame target association processing. The appearance-motion model is used to match the trajectory with the high-scoring targets, and the motion model is used to match the trajectory with the low-scoring targets. The test results of the UAV aerial dataset show that the method proposed in this paper improves the tracking accuracy and can effectively handle the ID Switch and track fragment problems caused by the target occlusion.

Original languageEnglish
Title of host publicationProceedings - 2022 Chinese Automation Congress, CAC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2200-2205
Number of pages6
ISBN (Electronic)9781665465335
DOIs
StatePublished - 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

  • Aerial Images
  • ID Switch
  • MOT
  • ReID-Byte

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