Method

Behavioral Multi Person Tracker [la] [on] [Be-Track]


Submitted on 6 Dec. 2017 11:53 by
Martin Dimitrievski (IPI/TELIN)

Running time:0.02 s
Environment:GPU @ 1.5 Ghz (C/C++)

Method Description:
Method under review
Parameters:
Method under review
Latex Bibtex:
Method under review

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 50.39 % 72.85 % 51.40 % 91.80 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
PEDESTRIAN 60.43 % 87.31 % 71.42 % 14059 2043 9207 18.37 % 18268 328

Benchmark MT PT ML IDS FRAG
PEDESTRIAN 25.43 % 46.74 % 27.84 % 235 967

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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