The Way They Move: Tracking Multiple Targets with Similar Appearance

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

Short name:

SMOT_16

Benchmark:

Description:

We introduce a computationally efficient algorithm for
multi-object tracking by detection that addresses four main
challenges: appearance similarity among targets, missing
data due to targets being out of the field of view or oc-
cluded behind other objects, crossing trajectories, and cam-
era motion. The proposed method uses motion dynamics as
a cue to distinguish targets with similar appearance, min-
imize target mis-identification and recover missing data.
Computational efficiency is achieved by using a General-
ized Linear Assignment (GLA) coupled with efficient proce-
dures to recover missing data and estimate the complexity
of the underlying dynamics. The proposed approach works
with tracklets of arbitrary length and does not assume a
dynamical model a priori, yet it captures the overall mo-
tion dynamics of the targets. Experiments using challenging
videos show that this framework can handle complex target
motions, non-stationary cameras and long occlusions, on
scenarios where appearance cues are not available or poor.

Hardware:

2.6 GHz, 16 Cores

Detector:

Public

Processing:

Batch

Last submitted:

February 29, 2016 (1 year ago)

Published:

November 30, -0001 at 00:00:00 CET

Submissions:

1

Open source:

Yes

Project page / code:

Reference:

C. Dicle, O. Camps, M. Sznaier. The Way They Move: Tracking Targets with Similar Appearance. In ICCV, 2013.

Benchmark performance:

MOTAMOTPFAFMTMLFPFNID Sw.FragSpecificationsDetector
29.775.22.95.3 % 47.7 % 17,426107,5523,1084,4832.6 GHz, 16 CoresPublic

Detailed performance:

Sequence MOTA MOTP FAF GT MT ML FP FN ID Sw Frag
MOT16-0121.772.00.9238.7 % 39.1 % 4034,50998160
MOT16-0335.075.38.614812.2 % 21.6 % 12,97453,1651,8532,632
MOT16-0632.173.30.22214.5 % 52.9 % 1957,455182342
MOT16-0726.773.51.7541.9 % 35.2 % 83810,832296501
MOT16-0820.878.81.9631.6 % 44.4 % 1,18611,752315316
MOT16-1227.076.70.9867.0 % 50.0 % 7875,074194210
MOT16-1413.574.31.41641.2 % 69.5 % 1,04314,765170322

Raw data:


SMOT_16