Method

Fast Fusion tracker [FFtracker]


Submitted on 4 Nov. 2021 15:25 by
Xiyang Wang (Chongqing University (CQU SLAMMOT Team))

Running time:34.5 s
Environment:>8 cores @ 2.5 Ghz (Python)

Method Description:
A fast fusion method of tracker based on camera and
lidar.
Parameters:
TBD
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 70.63 % 68.71 % 73.08 % 76.93 % 79.47 % 75.45 % 89.81 % 86.61 %

Benchmark TP FP FN
CAR 30444 3948 2849

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 79.82 % 84.92 % 80.24 % 142 66.47 %

Benchmark MT rate PT rate ML rate FRAG
CAR 67.69 % 23.54 % 8.77 % 445

Benchmark # Dets # Tracks
CAR 33293 1182

This table as LaTeX