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Development of a multi-object tracking algorithm with untrained features of object matching
V.A. Gorbachev 1, V.F. Kalugin 1

1 State Research Institute of Aviation Systems,
125167, Moscow, Russia, Viktorenko str. 7

 PDF, 2530 kB

DOI: 10.18287/2412-6179-CO-1275

Pages: 1002-1010.

Full text of article: Russian language.

Abstract:
The problem of multiple object tracking is one of the most difficult tasks in computer vision. The article is devoted to a task of multiple object tracking on video footage received from an unmanned aerial vehicle. Unlike a static camera platform, the mobile platform causes an accidental camera movement, which leads to sudden changes in the position, angle and scale of objects. Such aspects considerably hinder efficient object tracking. In this paper, we explore the possibilities of improving the tracking quality in the case of camera movements. We significantly outperform ByteTrack algorithm, one of the best tracking algorithms for the MOT Challenge dataset, on the Visdrone 2019 dataset.

Keywords:
multiple object tracking, YOLO v5, ByteTrack, Kalman filter, Visdrone 2019, UAV.

Citation:
Gorbachev VA, Kalugin VF. Development of a multi-object tracking algorithm with untrained features of object matching. Computer Optics 2023; 47(6): 1002-1010. DOI: 10.18287/2412-6179-CO-1275.

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