The KITTI Vision Benchmark Suite

Multi-target tracking is performed as minimization
of a continuous energy that includes many important
aspects. Besides the image evidence, the energy
function takes into account physical constraints,
such as target dynamics, mutual exclusion, and track
persistence. A suitable optimization scheme that
alternates between continuous conjugate gradient
descent and discrete trans-dimensional jump moves is
able to find strong local minima of the proposed
non-convex energy.

Provided L-SVM detections with a score above 0.0
servce as input, along with the following
parameters:
wtEdyn=1
wtEexc=0.5
wtEper=0.5
wtEreg=0.25
lambda=0.15

The ooptimization is initialized with the Dynamic
Programming [DP] solution of [Pirsiavash et al.].
No appearance and no occlusion modeling is used in
this setting.

@article{Milan2014PAMI,
author = {Milan, A. and Roth, S. and Schindler, K.},
title = {Continuous Energy Minimization for Multitarget Tracking},
volume = {36},
issn = {0162-8828},
doi = {10.1109/TPAMI.2013.103},
number = {1},
journal = {IEEE TPAMI},
year = {2014},
pages = {58--72}
}