Method

Fast Metric Multi-Object Vehicle Tracking [FMMOVT]


Submitted on 13 May. 2015 22:11 by
Francisco Alexandre Ribeiro de Alencar (University of Sao Paulo)

Running time:0.05 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
Simple, effective and fast metric multi-object
vehicle tracking system for dynamical environment
comprehension.
Parameters:
threshold = 0.5
Latex Bibtex:
@article{Alencar2015LARS,
booktitle={Latin American Robotics Symposium
(LARS), 2015},
author={Alencar, F. A. R. and Massera, C. A. and
Ridel, D. A. and Wolf, D.},
title={Fast Metric Multi-Object Vehicle Tracking
for Dynamical Environment Comprehension},
year={2015},
pages={6},
}

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 31.88 % 77.68 % 33.36 % 86.20 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
CAR 49.56 % 77.82 % 60.56 % 17595 5014 17904 45.07 % 23562 2063

Benchmark MT PT ML IDS FRAG
CAR 21.38 % 43.69 % 34.92 % 511 930

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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