Source code for the paper "A labeled random finite set online multi-object tracker for video data".
Kim, D. Y., Vo, B. N., Vo, B. T., & Jeon, M. (2019). A labeled random finite set online multi-object tracker for video data. Pattern Recognition, 90, 377-389.
FairMOT detector with format {frame}, {top},{left},{bottom},{right},{confidence score}, frame index starting from zero
MOT15: mot15_fairmot128_conf0.3_tlbr, loaded "fairmot_dla34.pth" pre-trained weight, obtain detection with a confidence score higher than 0.3
MOT16: mot16_fairmot128_conf0.5_tlbr, loaded "fairmot_dla34.pth" pre-trained weight, obtain detection with a confidence score higher than 0.5
Zhang, Y., Wang, C., Wang, X., Zeng, W., & Liu, W. (2021). FairMOT: On the fairness of detection and re-identification in multiple object tracking. International Journal of Computer Vision, 129, 3069-3087.
Saved with MOTChallenge format {frame}, {id}, {bb_left}, {bb_top}, {bb_width}, {bb_height}, 1,-1,-1,-1