Method

Tensor [TENSOR]
[Anonymous Submission]

Submitted on 8 Oct. 2017 16:54 by
[Anonymous Submission]

Running time:0.04 s
Environment:1 core @ 2.5 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 71.18 % 79.15 % 72.39 % 85.56 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
CAR 80.08 % 94.09 % 86.52 % 30477 1915 7579 17.21 % 36127 1382

Benchmark MT PT ML IDS FRAG
CAR 47.85 % 40.46 % 11.69 % 418 947

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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