TFMOT: Joint Cost Minimization for Multi-Object Tracking


Benchmark:

Short name:

TFMOT

Detector:

Public

Description:

n/a

Project page / code:

n/a

Reference:

M. Abhijeet Boragule. Joint Cost Minimization for Multi-Object Tracking. In 2017 IEEE International Conference on Advanced Vide and Signale Based Surveillance, 2017.

Processing:

Online

Last submitted:

March 21, 2017 (3 years ago)

Published:

March 29, 2018 at 10:08:33 CET

Submissions:

3

Open source:

No

Hardware:

3.3 GHz 1 core.

Benchmark performance:

Sequence MOTA IDF1 MOTP MT ML FP FN ID Sw.
2D MOT 201523.832.371.335.0447.04,53341,873404

Detailed performance:

Sequence MOTA IDF1 MOTP MT ML FP FN ID Sw.
ADL-Rundle-117.335.372.96.011.02,1945,44263
ADL-Rundle-335.038.173.92.012.05036,04959
AVG-TownCentre18.028.370.312.0152.01585,66337
ETH-Crossing16.222.875.00.019.068305
ETH-Jelmoli29.241.372.94.021.01251,65616
ETH-Linthescher6.411.273.12.0180.0178,3308
KITTI-1632.239.072.50.05.0561,08117
KITTI-1922.840.464.53.024.06323,46629
PETS09-S2L238.432.469.03.011.05295,262145
TUD-Crossing49.458.674.43.03.0445086
Venice-115.124.873.70.09.02693,58619

Raw data:


TFMOT