Method

NTU-Tracker [NTU-Tracker]
[Anonymous Submission]

Submitted on 19 May. 2025 10:59 by
[Anonymous Submission]

Running time:0.01 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
a new tracker with new representation and metrics
Parameters:
na
Latex Bibtex:

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 91.87 % 86.87 % 92.00 % 89.54 %

Benchmark recall precision F1 TP FP FN FAR #objects #trajectories
CAR 94.56 % 98.42 % 96.45 % 37359 601 2150 5.40 % 43163 696

Benchmark MT PT ML IDS FRAG
CAR 87.54 % 4.46 % 8.00 % 44 72

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.


eXTReMe Tracker