fff versus non-fff weighting in Hungarian algorithm

[djr2015]

From my understanding of https://github.com/YuliangXiu/PoseFlow/blob/4d2a78dfb4928335b4a8b2e76d4bb3b0b4a9a562/utils.py#L157 , this codebase performs pose tracking by matching bboxes & associated poses between frames based on a weighted sum of various distance metrics elaborated from object- and keypoint-level bbox IoUs as well as the shared ORB features contained within these bboxes.

It also seems like the bitartite matching graph is between a) all bboxes in frame t+1 and b) the most recent bboxes associated with each of the object tracks discovered thus far ( in frames <= t) based on https://github.com/MVIG-SJTU/AlphaPose/blob/9dafbb2259a36bf92df87042863eba7f543d3cf9/PoseFlow/utils.py#L93.

I was wondering why these distance metrics are weighted differently ( https://github.com/YuliangXiu/PoseFlow/blob/4d2a78dfb4928335b4a8b2e76d4bb3b0b4a9a562/tracker-general.py#L112 ) depending on whether the boxes in b) were from frame t or not? It seems like the ORB-based matching criteria are given weight 0 for b) boxes from frame t and 1 otherwise.