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 HOTA tracking metrics (HOTA, DetA, AssA, DetRe, DetPr, AssRe, AssPr, LocA) [1] as well as the CLEARMOT, MT/PT/ML, identity switches, and fragmentation [2,3] metrics. The tables below show all of these metrics.


Benchmark HOTA DetA AssA DetRe DetPr AssRe AssPr LocA
CAR 34.35 % 33.80 % 35.39 % 39.20 % 62.79 % 39.66 % 75.42 % 80.40 %

Benchmark TP FP FN
CAR 16472 17920 5000

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 31.23 % 77.93 % 33.36 % 731 20.66 %

Benchmark MT rate PT rate ML rate FRAG
CAR 21.39 % 43.69 % 34.92 % 612

Benchmark # Dets # Tracks
CAR 21472 1836

This table as LaTeX

This figure as: png pdf

[1] J. Luiten, A. Os̆ep, P. Dendorfer, P. Torr, A. Geiger, L. Leal-Taixé, B. Leibe: HOTA: A Higher Order Metric for Evaluating Multi-object Tracking. IJCV 2020.
[2] K. Bernardin, R. Stiefelhagen: Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. JIVP 2008.
[3] Y. Li, C. Huang, R. Nevatia: Learning to associate: HybridBoosted multi-target tracker for crowded scene. CVPR 2009.


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