Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Video based real-time positional tracker   We propose a system that uses video as the input to track the position of
objects relative to their surrounding environment in real-time. The neural
network employed is trained on a 100% synthetic dataset coming from our own
automated generator. The positional tracker relies on a range of 1 to n video
cameras placed around an arena of choice.
  The system returns the positions of the tracked objects relative to the
broader world by understanding the overlapping matrices formed by the cameras
and therefore these can be extrapolated into real world coordinates.
  In most cases, we achieve a higher update rate and positioning precision than
any of the existing GPS-based systems, in particular for indoor objects or
those occluded from clear sky.

9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat