JPDA with optimized Parameter

TUD-Crossing PETS09-S2L2 ETH-Jelmoli ETH-Linthescher ETH-Crossing AVG-TownCentre ADL-Rundle-1 ADL-Rundle-3 KITTI-16 KITTI-19

Short name:

JPDA_OP

Benchmark:

Description:

Try to find the optimal parameters for the JPDA algorithm with an evolutional algorithm.

Hardware:

2.6 GHz, 1 Core

Detector:

Public

Processing:

Online

Last submitted:

December 04, 2018 (11 days ago)

Published:

November 20, 2018 at 18:36:21 CET

Submissions:

3

Open source:

No

Project page / code:

Reference:

Anonymous submission

Benchmark performance:

MOTAMOTPFAFMTMLFPFNID Sw.FragSpecificationsDetector
3.670.30.20.4 % 96.1 % 1,02458,189291192.6 GHz, 1 CorePublic
IDF1ID PrecisionID Recall
7.557.84.0

Detailed performance:

Sequence MOTA IDF1 MOTP FAF GT MT ML FP FN ID Sw Frag
TUD-Crossing0.00.00.00.0130.0 % 100.0 % 01,10200
PETS09-S2L26.710.868.80.5420.0 % 85.7 % 2288,756944
ETH-Jelmoli1.74.669.60.0450.0 % 95.6 % 192,47602
ETH-Linthescher0.81.562.30.01970.5 % 99.5 % 08,86300
ETH-Crossing0.00.00.00.0260.0 % 100.0 % 01,00300
AVG-TownCentre0.00.00.00.02260.0 % 100.0 % 07,14800
ADL-Rundle-15.516.170.31.2326.3 % 71.9 % 5988,1771649
ADL-Rundle-35.97.976.20.0440.0 % 93.2 % 259,53446
KITTI-163.14.770.90.1170.0 % 94.1 % 121,63603
KITTI-194.09.064.20.0620.0 % 91.9 % 475,082013
Venice-11.26.368.90.2170.0 % 94.1 % 954,41202

Raw data:

n/a


JPDA_OP