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microsoft / FairMOT

This project provides an official implementation of our recent work on real-time multi-object tracking in videos. The previous works conduct object detection and tracking with two separate models so they are very slow. In contrast, we propose a one-stage solution which does detection and tracking with a single network by elegantly solving the alignment problem. The resulting approach achieves groundbreaking results in terms of both accuracy and speed: (1) it ranks first among all the trackers on the MOT challenges; (2) it is significantly faster than the previous state-of-the-arts. In addition, it scales gracefully to handle a large number of objects.
MIT License
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kalman init #2

Open kuku-sichuan opened 4 years ago

kuku-sichuan commented 4 years ago

why the init of kalman filter's std is: std = [ 2 self._std_weight_position measurement[3], 2 self._std_weight_position measurement[3], 1e-2, 2 self._std_weight_position measurement[3], 10 self._std_weight_velocity measurement[3], 10 self._std_weight_velocity measurement[3], 1e-5, 10 self._std_weight_velocity measurement[3]]

could you tell some reason or source ?

gau-nernst commented 3 years ago

I believe this is taken directly from SORT/DeepSORT. You can check those repos and the corresponding papers for more information. But in general I think the values were just slightly tuned by the DeepSORT author and no one bothers to modify them when they use Kalman filter in other trackers.