Visual tracking with confidence correction based on log-polar mapping

Qifeng Liang; Peiqiang Liu; Jingyi Fu; Zhiyong An

doi:10.1117/12.2681119

8 June 2023 Visual tracking with confidence correction based on log-polar mapping

Qifeng Liang, Peiqiang Liu, Jingyi Fu, Zhiyong An

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127073D (2023) https://doi.org/10.1117/12.2681119
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

Transformer-based object tracking has become mainstream due to its high tracking performance at present. Most transformer-based trackers still classify the foreground and background and then calculate the bounding box by regression. However, we find that the classification confidence of transformer tracking is inaccurate. This leads to the bounding box with the highest confidence is not the closest to the ground truth. To address the problem, we propose a robust visual tracking approach with confidence correction using log-polar mapping. By correcting the confidence, the transformer tracking can obtain the best bounding box and improve the accuracy of the tracker. Extensive experiments on OTB2015, UAV123, and UAV20L show that our tracker is superior to the state-of-the-art trackers.

Citation Download Citation

Qifeng Liang, Peiqiang Liu, Jingyi Fu, and Zhiyong An "Visual tracking with confidence correction based on log-polar mapping", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127073D (8 June 2023); https://doi.org/10.1117/12.2681119

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