Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Egocentric Human Segmentation for Mixed Reality   The objective of this work is to segment human body parts from egocentric
video using semantic segmentation networks. Our contribution is two-fold: i) we
create a semi-synthetic dataset composed of more than 15, 000 realistic images
and associated pixel-wise labels of egocentric human body parts, such as arms
or legs including different demographic factors; ii) building upon the
ThunderNet architecture, we implement a deep learning semantic segmentation
algorithm that is able to perform beyond real-time requirements (16 ms for 720
x 720 images). It is believed that this method will enhance sense of presence
of Virtual Environments and will constitute a more realistic solution to the
standard virtual avatars.

34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
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The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
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The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph