Method

SearchTrack [SearchTrack]


Submitted on 22 Dec. 2021 08:03 by
ZhongMin Tsai ( Communication and Multimedia Laboratory, National Taiwan University)

Running time:0.19 s
Environment:GPU @ 2.5 Ghz (Python)

Method Description:
A Search-Based Tracker with Position-Aware Motion
Model
Parameters:
none
Latex Bibtex:

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 71.46 % 76.76 % 67.12 % 81.16 % 87.00 % 71.44 % 85.84 % 88.08 %
PEDESTRIAN 57.63 % 63.66 % 53.12 % 67.59 % 77.78 % 58.96 % 73.36 % 80.89 %

Benchmark TP FP FN
CAR 33413 3347 880
PEDESTRIAN 17356 3341 631

Benchmark MOTSA MOTSP MODSA IDSW sMOTSA
CAR 86.83 % 86.83 % 88.50 % 616 74.85 %
PEDESTRIAN 78.92 % 78.16 % 80.81 % 390 60.61 %

Benchmark MT rate PT rate ML rate FRAG
CAR 80.18 % 18.32 % 1.50 % 727
PEDESTRIAN 60.37 % 35.19 % 4.44 % 661

Benchmark # Dets # Tracks
CAR 34293 893
PEDESTRIAN 17987 403

This table as LaTeX