This toolkit is used to evaluate general thermal infrared (TIR) trackers on the TIR object tracking benchmark, LSOTB-TIR, which consists of a large-scale training dataset and an evaluation dataset with a total of 1,400 TIR image sequences and more than 600K frames. To evaluate a TIR tracker on different attributes, we define 4 scenario attributes and 12 challenge attributes in the evaluation dataset. By releasing LSOTB-TIR, we encourage the community to develop deep learning based TIR trackers and evaluate them fairly and comprehensively. Paper, Supplementary materials
sequences
folder.results
folder.run_evaluation.m
and run_speed.m
to draw the result plots.configTrackers.m
and then use main_running_one.m
to run your own tracker on the benchmark.
Feedbacks and comments are welcome! Feel free to contact us via liuqiao.hit@gmail.com or liuqiao@stu.hit.edu.cn