A robust one-shot online multi-object tracking method

Wuzhou Quan

doi:10.1117/12.2680928

8 June 2023 A robust one-shot online multi-object tracking method

Wuzhou Quan

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127071Y (2023) https://doi.org/10.1117/12.2680928
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

Current studies suggest that one-shot multi-object tracking approaches are as competitive as methods that separate inference into two branches. However, current methods neglect the inherent differences and relationships between tasks. To address this question, we propose RoTrack, which incorporates a novel inference network and efficient association approach. Our network module learns both inter-task associations and difference to alleviate inference inequality. We introduce the coordinate associating opportunity (CAO) strategy, which employs fair voting to avoid errors resulting from manual selection of association bases. We evaluate our algorithm on public MOT Challenge datasets and demonstrate outstanding results. Experiments show that RoTrack can well deal with the above-mentioned problems in the field of multi-object tracking.

Citation Download Citation

Wuzhou Quan "A robust one-shot online multi-object tracking method", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127071Y (8 June 2023); https://doi.org/10.1117/12.2680928

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