Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A grid-point detection method based on U-net for a structured light
  system   Accurate detection of the feature points of the projected pattern plays an
extremely important role in one-shot 3D reconstruction systems, especially for
the ones using a grid pattern. To solve this problem, this paper proposes a
grid-point detection method based on U-net. A specific dataset is designed that
includes the images captured with the two-shot imaging method and the ones
acquired with the one-shot imaging method. Among them, the images in the first
group after labeled as the ground truth images and the images captured at the
same pose with the one-shot method are cut into small patches with the size of
64x64 pixels then feed to the training set. The remaining of the images in the
second group is the test set. The experimental results show that our method can
achieve a better detecting performance with higher accuracy in comparison with
the previous methods.

3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph