Method

Joint Constraints in Spatial and Temporal Domain [on] [JCSTD]


Submitted on 27 Apr. 2017 12:38 by
Tian Wei (MRT)

Running time:0.07 s
Environment:1 core @ 2.7 Ghz (C++)

Method Description:
Joint Constraints in Spatial and Temporal Domain
Parameters:
1 core
Latex Bibtex:
@ARTICLE{Tian2019MOT,
author={Wei Tian and Martin Lauer and Long Chen},
journal={IEEE Transactions on Intelligent
Transportation Systems},
title={Online Multi-Object Tracking Using Joint
Domain Information in Traffic Scenarios},
year={2019},
volume={},
number={},
pages={1-11},
doi={10.1109/TITS.2019.2892413},
ISSN={1524-9050},
month={Jan.},
}

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 65.94 % 65.37 % 67.03 % 68.49 % 82.42 % 71.02 % 82.25 % 84.03 %
PEDESTRIAN 39.44 % 34.20 % 45.79 % 36.15 % 69.39 % 49.38 % 69.00 % 76.23 %

Benchmark TP FP FN
CAR 28175 6217 405
PEDESTRIAN 11174 11976 885

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 80.24 % 81.85 % 80.75 % 173 65.38 %
PEDESTRIAN 43.42 % 71.72 % 44.45 % 236 29.78 %

Benchmark MT rate PT rate ML rate FRAG
CAR 57.08 % 35.08 % 7.85 % 700
PEDESTRIAN 18.56 % 47.08 % 34.36 % 975

Benchmark # Dets # Tracks
CAR 28580 653
PEDESTRIAN 12059 245

This table as LaTeX

This figure as: png pdf

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.


eXTReMe Tracker