Affiliation:
1. School of Aerospace Engineering Xi'an Jiaotong University Xi'an China
2. Unmanned System Research Institute Northwestern Polytechnical University Xi'an China
Abstract
AbstractTo address the issue of tracking drift and failures in thermal infrared (TIR) tracking tasks caused by target occlusion, this study proposes an anti‐occlusion TIR target tracker named AODiMP‐TIR. This approach involves an anti‐occlusion strategy that relies on target occlusion status determination and trajectory prediction. This enables the prediction of the target's current position when it is identified as occluded, ensuring swift recapture upon reappearance. A criterion is introduced for occlusion status determination based on the classification response map of SuperDiMP. Additionally, a trajectory mapping module designed to decouple target motion from camera motion is presented, enhancing the precision of trajectory prediction. Comparative experiments with other state‐of‐the‐art trackers are conducted on the large‐scale high‐diversity thermal infrared object tracking benchmark (LSOTB‐TIR), LSOTB‐TIR100, and thermal infrared pedestrian tracking benchmark (PTB‐TIR) datasets. The results indicate that the AODiMP‐TIR performs well across all three datasets, particularly exhibiting outstanding performance in occlusion sequences. Furthermore, ablation study experiments confirm the effectiveness of the anti‐occlusion strategy, occlusion determination criterion and trajectory mapping module.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shaanxi Province
Publisher
Institution of Engineering and Technology (IET)