SVT: Multi-View Tracker

PETS09-S2L2


Benchmark:

Short name:

SVT

Detector:

Public

Description:

Incorporating multiple cameras is an effective solution to improve the performance and robustness of multitarget tracking to occlusion and appearance ambiguities. In this paper,we propose a new multi-camera multi-target tracking method based on a space-time-view hyper-graph that encodes higher-order constraints (i.e., beyond pairwise relations) on 3D geometry, appearance, motion continuity, and trajectory smoothness among 2D tracklets within and across different camera views.We solve tracking in each single view
and reconstruction of tracked trajectories in 3D environment simultaneously by formulating the problem as an efficient search of dense sub-hypergraphs on the space-time-view hyper-graph using a sampling based approach.

Project page / code:

n/a

Reference:

Longyin Wen, Zhen Lei, Ming-Ching Chang, Honggang Qi, Siwei Lyu. Multi-Camera Multi-Target Tracking with Space-Time-View Hyper-graph. IJCV, 2016.

Processing:

Batch

Last submitted:

December 10, 2015 (4 years ago)

Published:

February 20, 2017 at 18:52:50 CET

Submissions:

3

Open source:

No

Hardware:

2.7GHZ, 1 Core

Runtime:

1.9 Hz

Benchmark performance:

Sequence MOTA IDF1 MOTP MT ML FP FN Recall Precision FAF ID Sw. Frag
3D MOT 201534.20.055.830 (11.2)68 (25.4)3,0577,45455.675.33.5532 (9.6)611 (11.0)

Detailed performance:

Sequence MOTA IDF1 MOTP MT ML FP FN Recall Precision FAF ID Sw. Frag
AVG-TownCentre0.00.00.000000.00.00.000
PETS09-S2L20.00.00.000000.00.00.000

Raw data: