Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multiple object tracking with context awareness   Multiple people tracking is a key problem for many applications such as
surveillance, animation or car navigation, and a key input for tasks such as
activity recognition. In crowded environments occlusions and false detections
are common, and although there have been substantial advances in recent years,
tracking is still a challenging task. Tracking is typically divided into two
steps: detection, i.e., locating the pedestrians in the image, and data
association, i.e., linking detections across frames to form complete
trajectories.
  For the data association task, approaches typically aim at developing new,
more complex formulations, which in turn put the focus on the optimization
techniques required to solve them. However, they still utilize very basic
information such as distance between detections. In this thesis, I focus on the
data association task and argue that there is contextual information that has
not been fully exploited yet in the tracking community, mainly social context
and spatial context coming from different views.

8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga