Online Multi-object Visual Tracking using a GM-PHD Filter with Deep Appearance Learning

MOT16-01 MOT16-03 MOT16-06 MOT16-07 MOT16-08 MOT16-12 MOT16-14

Short name:

GM_PHD_DAL

Benchmark:

Description:

n/a

Hardware:

3 GHZ, 1 Core

Detector:

Public

Processing:

Online

Last submitted:

March 21, 2019 (3 months ago)

Published:

February 11, 2019 at 22:59:20 CET

Submissions:

2

Open source:

No

Project page / code:

n/a

Reference:

https://www.researchgate.net/publication/333521185_Online_Multi-object_Visual_Tracking_using_a_GM-PHD_Filter_with_Deep_Appearance_Learning

Benchmark performance:

MOTAMOTPFAFMTMLFPFNID Sw.FragSpecificationsDetector
35.176.60.47.0 % 51.4 % 2,350111,8864,0475,3383 GHZ, 1 CorePublic
IDF1ID PrecisionID Recall
26.646.618.6

Detailed performance:

Sequence MOTA IDF1 MOTP FAF GT MT ML FP FN ID Sw Frag
MOT16-0122.019.773.60.1238.7 % 56.5 % 634,818107170
MOT16-0340.927.476.70.71488.1 % 29.7 % 1,00958,3482,3933,121
MOT16-0640.236.874.20.12218.1 % 50.7 % 1256,457313371
MOT16-0729.523.674.90.7547.4 % 48.1 % 33210,710472638
MOT16-0828.525.380.30.4637.9 % 46.0 % 23711,498229310
MOT16-1236.034.877.70.3869.3 % 51.2 % 3134,842155230
MOT16-1414.215.675.60.41642.4 % 74.4 % 27115,213378498

Raw data:

n/a


GM_PHD_DAL