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fff versus non-fff weighting in Hungarian algorithm #22

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djr2015 opened this issue Aug 11, 2019 · 0 comments
Open

fff versus non-fff weighting in Hungarian algorithm #22

djr2015 opened this issue Aug 11, 2019 · 0 comments

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@djr2015
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djr2015 commented Aug 11, 2019

From my understanding of

def best_matching_hungarian(all_cors, all_pids_info, all_pids_fff, track_vid_next_fid, weights, weights_fff, num, mag):
, 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 (

weights = [1,2,1,2,0,0]
) 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.

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