DCO_X: Discrete-Continuous Energy Minimization with Exclusion

TUD-Crossing


Benchmark:

Short name:

DCO_X

Detector:

Public

Description:

We formulate multi-target tracking as a discrete-continuous optimization problem that handles both data association and trajectory estimation in its respective natural domain and allows leveraging powerful methods for multi-model fitting. Data association is performed using discrete optimization with label costs, yielding near optimality. Trajectory estimation is posed as a continuous fitting problem which is used in turn to update the label costs.

Reference:

A. Milan, K. Schindler, S. Roth. Multi-Target Tracking by Discrete-Continuous Energy Minimization. In IEEE PAMI, 2016.

Last submitted:

June 02, 2015 (5 years ago)

Published:

July 28, 2015 at 17:01:02 CET

Submissions:

2

Project page / code:

Open source:

Yes

Hardware:

2.7 GHz, 1 Core

Runtime:

0.3 Hz

Benchmark performance:

Sequence MOTA IDF1 MOTP MT ML FP FN Recall Precision FAF ID Sw. Frag
2D MOT 201519.631.571.437 (5.1)396 (54.9)10,65238,23237.868.51.8521 (13.8)819 (21.7)

Detailed performance:

Sequence MOTA IDF1 MOTP MT ML FP FN Recall Precision FAF ID Sw. Frag
ADL-Rundle-10.00.00.000000.00.00.000
ADL-Rundle-30.00.00.000000.00.00.000
AVG-TownCentre0.00.00.000000.00.00.000
ETH-Crossing0.00.00.000000.00.00.000
ETH-Jelmoli0.00.00.000000.00.00.000
ETH-Linthescher0.00.00.000000.00.00.000
KITTI-160.00.00.000000.00.00.000
KITTI-190.00.00.000000.00.00.000
PETS09-S2L20.00.00.000000.00.00.000
TUD-Crossing0.00.00.000000.00.00.000
Venice-10.00.00.000000.00.00.000

Raw data: