Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Local Frequency Interpretation and Non-Local Self-Similarity on Graph
  for Point Cloud Inpainting   As 3D scanning devices and depth sensors mature, point clouds have attracted
increasing attention as a format for 3D object representation, with
applications in various fields such as tele-presence, navigation and heritage
reconstruction. However, point clouds usually exhibit holes of missing data,
mainly due to the limitation of acquisition techniques and complicated
structure. Further, point clouds are defined on irregular non-Euclidean
domains, which is challenging to address especially with conventional signal
processing tools. Hence, leveraging on recent advances in graph signal
processing, we propose an efficient point cloud inpainting method, exploiting
both the local smoothness and the non-local self-similarity in point clouds.
Specifically, we first propose a frequency interpretation in graph nodal
domain, based on which we introduce the local graph-signal smoothness prior in
order to describe the local smoothness of point clouds. Secondly, we explore
the characteristics of non-local self-similarity, by globally searching for the
most similar area to the missing region. The similarity metric between two
areas is defined based on the direct component and the anisotropic graph total
variation of normals in each area. Finally, we formulate the hole-filling step
as an optimization problem based on the selected most similar area and
regularized by the graph-signal smoothness prior. Besides, we propose
voxelization and automatic hole detection methods for the point cloud prior to
inpainting. Experimental results show that the proposed approach outperforms
four competing methods significantly, both in objective and subjective quality.

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The categories of this paper are: acc-phys
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The categories of this paper are: q-alg
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The categories of this paper are: econ
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The categories of this paper are: math-ph
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The categories of this paper are: solv-int
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The categories of this paper are: mtrl-th
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The categories of this paper are: ao-sci
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The categories of this paper are: stat
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The categories of this paper are: math
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The categories of this paper are: atom-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: adap-org
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The categories of this paper are: eess
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The categories of this paper are: nucl-th
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The categories of this paper are: hep-lat
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The categories of this paper are: chao-dyn