Lightweight Siamese network-based single-target tracking algorithm for pedestrians

Cong Sun; Yubing Dong; Mingjing Li; Dong Pan

doi:10.1117/12.2668485

20 April 2023 Lightweight Siamese network-based single-target tracking algorithm for pedestrians

Cong Sun, Yubing Dong, Mingjing Li, Dong Pan

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126022U (2023) https://doi.org/10.1117/12.2668485
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

Aiming at the problem of slow running speed of pedestrian single-target tracking task using SiamBAN algorithm under limited hardware conditions, this paper proposes a lightweight pedestrian single-target tracking network GhostSiamBAN. Specifically, we use GhostModule to build a new lightweight backbone network to replace the original Resnet50. The evaluation on OTB2015 and VOT2018 shows that our method can well balance the tracking accuracy and speed. Compared with SiamBAN, the test results of pedestrian single target tracking sequence on Nvidia GTX 1050 show that the average running speed of our method is about 26fps with an accuracy loss of about 5.46%, and the speed is increased by nearly 271.4%

Citation Download Citation

Cong Sun, Yubing Dong, Mingjing Li, and Dong Pan "Lightweight Siamese network-based single-target tracking algorithm for pedestrians", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126022U (20 April 2023); https://doi.org/10.1117/12.2668485

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KEYWORDS

Detection and tracking algorithms

Convolution

Education and training

Feature extraction

Video

Deep learning

Mobile devices

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