Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Crowd Source Scene Change Detection and Local Map Update   As scene changes with time map descriptors become outdated, affecting VPS
localization accuracy. In this work, we propose an approach to detect
structural and texture scene changes to be followed by map update. In our
method - map includes 3D points with descriptors generated either via LiDAR or
SFM. Common approaches suffer from shortcomings: 1) Direct comparison of the
two point-clouds for change detection is slow due to the need to build new
point-cloud every time we want to compare; 2) Image based comparison requires
to keep the map images adding substantial storage overhead. To circumvent this
problems, we propose an approach based on point-clouds descriptors comparison:
1) Based on VPS poses select close query and map images pairs, 2) Registration
of query images to map image descriptors, 3) Use segmentation to filter out
dynamic or short term temporal changes, 4) Compare the descriptors between
corresponding segments.

27
The categories of this paper are: comp-gas
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph