Online Multiple Pedestrian Tracking with Deep Temporal Appearance Matching Association


Short name:

DD_TAMA19

Benchmark:

Description:

This is the journal extension of our conference paper. We substituted hand-crafted matching association weights to data-driven weights.

Hardware:

3.0GHZ, 1 Core, TITAN X

Detector:

Public

Processing:

Online

Last submitted:

June 13, 2019 (1 month ago)

Published:

June 16, 2019 at 00:00:00 CET

Submissions:

1

Open source:

No

Project page / code:

n/a

Reference:

Y. Yoon, D. Kim, K. Yoon, Y. Song, M. Jeon. Online Multiple Pedestrian Tracking using Deep Temporal Appearance Matching Association. In arXiv:1907.00831, 2019.

Benchmark performance:

MOTAMOTPFAFMTMLFPFNID Sw.FragSpecificationsDetector
47.677.68.527.2 % 23.6 % 38,194252,9342,4373,8873.0GHZ, 1 Core, TITAN XPublic
IDF1ID PrecisionID Recall
48.763.839.4

Detailed performance:

Sequence MOTA IDF1 MOTP FAF GT MT ML FP FN ID Sw Frag
CVPR19-0464.059.280.14.069238.7 % 13.0 % 8,225105,4999001,325
CVPR19-0626.132.871.715.22639.9 % 38.0 % 15,27980,8308141,420
CVPR19-0753.949.675.73.211134.2 % 13.5 % 1,86513,161237288
CVPR19-0813.826.069.915.91905.3 % 48.4 % 12,82553,444486854

Raw data:

n/a


DD_TAMA19