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Hi @realgump, thank you for your great work mvmhat.
When you apply multi view tracking with single view trackers,
you applied spatial association first(at frame_matching() and deep_sort/linear_assignment.py).
What is the intuition of applying spatial association first? Would this setting be appropriate for non-overlapping camera settings, too?
I wonder if you have experimented ablation study regarding the order of association.
The text was updated successfully, but these errors were encountered:
In my opinion, the tracking problem is typically an online task. For time-synchronized cameras, at time 0, there is only one frame from each camera. Therefore, we must apply spatial association and assign an ID to each person to initialize their tracklet. At time t > 0, as described in Algorithm 1, Lines 6-9 of Self-supervised Multi-view Multi-Human Association and Tracking, we first apply temporal association, followed by spatial association.
Any person unmatched during spatial association will be assigned a new ID, thus the algorithm suitable for non-overlapping camera settings as well.
Hi @realgump, thank you for your great work mvmhat.
When you apply multi view tracking with single view trackers,
you applied spatial association first(at
frame_matching()
anddeep_sort/linear_assignment.py
).What is the intuition of applying spatial association first? Would this setting be appropriate for non-overlapping camera settings, too?
I wonder if you have experimented ablation study regarding the order of association.
The text was updated successfully, but these errors were encountered: