Benchmark:

MOT20 | MOT17 |

Short name:

BBT

Detector:

Public

Description:

Tracker uses only bounding boxes, no visual information.
Bounding boxes are associated frame-to-frame maximizing the IOU metric.
Re-identification phase projects discovered tracks to past/future tracks within a time window of 50 frames and quantifies the track matching score.
Fragmented tracks with high matching score are linked together, missing bounding boxes interpolated.
The proposed tracker is extremely fast compared to visual-based methods, and more accurate than (similar-to-our-work method) IOU17 thanks to the re-identification phase,
The proposed tracker is used to discover inter-person relationships in videos.

Reference:

MTAP-D-20-01870 Tracking Subjects and Detecting Relationships in Crowded City Videos (under review)

Last submitted:

May 21, 2020 (4 years ago)

Published:

September 21, 2020 at 12:02:40 CET

Submissions:

2

Project page / code:

https://github.com/elicz/Multi-Subject-Tracking/

Open source:

Yes

Hardware:

Intel(R) Xeon(R) CPU E5-2620, 1 core

Runtime:

8.0 Hz

Benchmark performance:

Detailed performance:

Raw data:

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