Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Leveraging Structural Information to Improve Point Line Visual-Inertial
  Odometry   Leveraging line features can help to improve the localization accuracy of
point-based monocular Visual-Inertial Odometry (VIO) system, as lines provide
additional constraints. Moreover, in an artificial environment, some straight
lines are parallel to each other. In this paper, we designed a VIO system based
on points and straight lines, which divides straight lines into structural
straight lines (that is, straight lines parallel to each other) and
non-structural straight lines. In addition, unlike the orthogonal
representation using four parameters to represent the 3D straight line, we only
used two parameters to minimize the representation of the structural straight
line and the non-structural straight line. Furthermore, we designed a straight
line matching strategy based on sampling points to improve the efficiency and
success rate of straight line matching. The effectiveness of our method is
verified on both public datasets of EuRoc and TUM VI benchmark and compared
with other state-of-the-art algorithms.

0
The categories of this paper are: hep-ph
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom