Open xiaobaozi1996 opened 5 years ago
For sure it's not a perfect algorithm. You can try to twerk parameters on kalman_filter.py
Ok, I'll try it. By the way, Is there an effective method for tracking in the case of occlusion based on you knowledge
Hi @ortegatron - I'm having a similar issue where a track (ID) can be "stolen" if a person crosses in front of another, even just a little bit. Do you have any suggestions for the parameters to adjust that could help this happen less? I don't understand all of the math and such in the kalman_filter.py.
I guess you need to ponderate more the appearance matching.
Sorry to bother you again. Recently, I tested the code for my own dataset, but in the case of occlusion, ID is either changed or transferred. What parameters should I modify to avoid.