Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Tracking Road Users using Constraint Programming   In this paper, we aim at improving the tracking of road users in urban
scenes. We present a constraint programming (CP) approach for the data
association phase found in the tracking-by-detection paradigm of the multiple
object tracking (MOT) problem. Such an approach can solve the data association
problem more efficiently than graph-based methods and can handle better the
combinatorial explosion occurring when multiple frames are analyzed. Because
our focus is on the data association problem, our MOT method only uses simple
image features, which are the center position and color of detections for each
frame. Constraints are defined on these two features and on the general MOT
problem. For example, we enforce color appearance preservation over
trajectories and constrain the extent of motion between frames. Filtering
layers are used in order to eliminate detection candidates before using CP and
to remove dummy trajectories produced by the CP solver. Our proposed method was
tested on a motorized vehicles tracking dataset and produces results that
outperform the top methods of the UA-DETRAC benchmark.

29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
16
The categories of this paper are: stat
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat