Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Real-time Embedded Person Detection and Tracking for Shopping Behaviour
  Analysis   Shopping behaviour analysis through counting and tracking of people in
shop-like environments offers valuable information for store operators and
provides key insights in the stores layout (e.g. frequently visited spots).
Instead of using extra staff for this, automated on-premise solutions are
preferred. These automated systems should be cost-effective, preferably on
lightweight embedded hardware, work in very challenging situations (e.g.
handling occlusions) and preferably work real-time. We solve this challenge by
implementing a real-time TensorRT optimized YOLOv3-based pedestrian detector,
on a Jetson TX2 hardware platform. By combining the detector with a sparse
optical flow tracker we assign a unique ID to each customer and tackle the
problem of loosing partially occluded customers. Our detector-tracker based
solution achieves an average precision of 81.59% at a processing speed of 10
FPS. Besides valuable statistics, heat maps of frequently visited spots are
extracted and used as an overlay on the video stream.

36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
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The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
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The categories of this paper are: eess