Improved Object Tracking Algorithm Based on SiamBAN Tracker

doi:10.12068/j.issn.1005-3026.2023.09.002

Abstract

Abstract: The siamese network series tracker utilizes the similarity matching method for object tracking， but tracking drift can occur when similar distractors are encountered， leading to tracking failure. To solve this problem， based on the research of SiamBAN tracker， an improved algorithm is proposed. Major improvements include the addition of a centerness branch during training to reduce bounding box scores far from the object center， the introduction of the Focal Loss function， and a new screening strategy during inference to differentiate the target from similar distractors. Compared with the original， the success plot and precision plot of the improved algorithm are increased by 2.1% and 3% respectively on the OTB100 test set， and the success plot is 2.1% higher than the original on the GOT10k test set.

Key words: object tracking; SiamBAN; siamese network; distractor aware; neural network

CLC Number:

TP391

ZHENG Yan， ZHAO Jia-xu， BIAN Jie. Improved Object Tracking Algorithm Based on SiamBAN Tracker[J]. Journal of Northeastern University(Natural Science), 2023, 44(9): 1227-1233.

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