Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sensor-aided block matching algorithm for translational motion
  estimation through a depth map   A large number of cameras embedded on smart-phones, drones or inside cars
have a direct access to external motion sensing from gyroscopes and
accelerometers. On these power-limited devices, video compression must be of
low-complexity. For this reason, we propose a "Sensor-Aided Block Matching
Algorithm" which exploits the presence of a motion sensor synchronized with a
camera to reduce the complexity of the motion estimation process in an
inter-frame video codec. Our solution extends the work previously done on
rotational motion estimation to an original estimation of the translational
motion through a depth map. The proposed algorithm provides a complexity
reduction factor of approximately 2.5 compared to optimized block-matching
motion compensated inter-frame video codecs while maintaining high image
quality and providing as by-product a depth map of the scene.

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The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
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The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
1
The categories of this paper are: cs
12
The categories of this paper are: nucl-th