Method

Confidence Aware Pedestrian Tracking [on][st] [CAT]
[Anonymous Submission]

Submitted on 3 Jan. 2019 19:01 by
[Anonymous Submission]

Running time:
Environment:

Method Description:
Parameters:
Latex Bibtex:
@Article{isprs-annals-IV-2-W5-53-2019,
AUTHOR = {Nguyen, U. and Rottensteiner, F. and
Heipke, C.},
TITLE = {CONFIDENCE-AWARE PEDESTRIAN TRACKING
USING A STEREO CAMERA},
JOURNAL = {ISPRS Annals of Photogrammetry,
Remote Sensing and Spatial Information
Sciences},
VOLUME = {IV-2/W5},
YEAR = {2019},
PAGES = {53--60},
URL = {https://www.isprs-ann-photogramm-remote-
sens-spatial-inf-sci.net/IV-2-W5/53/2019/},
DOI = {10.5194/isprs-annals-IV-2-W5-53-2019}
}

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 52.35 % 71.57 % 53.24 % 91.17 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
PEDESTRIAN 60.87 % 89.47 % 72.45 % 14233 1676 9150 15.07 % 17003 595

Benchmark MT PT ML IDS FRAG
PEDESTRIAN 34.36 % 41.92 % 23.71 % 206 804

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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