| Citation: | ZHOU Qianli, ZHANG Wenjing, ZHAO Luping, et al. Cross-modal object tracking algorithm based on pedestrian attribute[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(9): 1635-1642. doi: 10.13700/j.bh.1001-5965.2020.0042(in Chinese)
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The accuracy and robustness of the object tracking algorithm have been influenced by the intra-class interference when tracking pedestrian. In this paper, we analyze the drawbacks of current tracking algorithms and propose a model to combine the visual feature and language priori to improve the performance of the tracker.The language guided branch is added to supervise the visual tracking branch by generating the attention, so the intra-class interference can be alleviated.We also propose a method to improve the accuracy of thecross-modal object tracking based on the location confidence instead of classification confidence for siamese trackers.To validate our method, we customize the dataset specialized for pedestrian tracking. The experiment shows the effectiveness of this model.
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