Method

IMMDP[on] [IMMDP]
[Anonymous Submission]

Submitted on 23 Nov. 2016 08:26 by
[Anonymous Submission]

Running time:0.19 s
Environment:4 cores @ >3.5 Ghz (Matlab + C/C++)

Method Description:
TBA
Parameters:
TBA
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
CAR 83.04 % 82.74 % 83.54 % 86.58 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
CAR 86.11 % 98.82 % 92.03 % 32668 391 5269 3.51 % 35646 701

Benchmark MT PT ML IDS FRAG
CAR 60.62 % 28.00 % 11.38 % 172 365

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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