Method

CT [CT]
[Anonymous Submission]

Submitted on 1 Jun. 2019 20:43 by
[Anonymous Submission]

Running time:0.5 s
Environment:1 core @ 3.0 Ghz (Matlab + C/C++)

Method Description:
Parameters:
Latex Bibtex:

Detailed Results

From all 29 test sequences, our benchmark computes the commonly used tracking metrics CLEARMOT, MT/PT/ML, identity switches, and fragmentations [1,2]. The tables below show all of these metrics.


Benchmark MOTA MOTP MODA MODP
PEDESTRIAN 29.06 % 70.41 % 30.00 % 90.77 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
PEDESTRIAN 63.88 % 65.50 % 64.68 % 14837 7815 8391 70.25 % 28821 566

Benchmark MT PT ML IDS FRAG
PEDESTRIAN 30.93 % 43.99 % 25.09 % 216 896

This table as LaTeX


[1] K. Bernardin, R. Stiefelhagen: Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. JIVP 2008.
[2] Y. Li, C. Huang, R. Nevatia: Learning to associate: HybridBoosted multi-target tracker for crowded scene. CVPR 2009.


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