Enhancement of 3D Point Cloud Contents Using 2D Image Super Resolution Network

被引:1
|
作者
Park, Seonghwan [1 ]
Kim, Junsik [1 ]
Hwang, Yonghae [1 ]
Suh, Doug Young [1 ]
Kim, Kyuheon [1 ]
机构
[1] Kyung Hee Univ, Yongin, South Korea
来源
JOURNAL OF WEB ENGINEERING | 2022年 / 21卷 / 02期
关键词
Point cloud; super resolution; deep learning network; 3D data; SEARCH; MPEG;
D O I
10.13052/jwe1540-9589.21213
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Media technology has been developed to give users a sense of immersion. Recent media using 3D spatial data, such as augmented reality and virtual reality, has attracted attention. A point cloud is a data format that consists of a number of points, and thus can express 3D media using coordinates and color information for each point. Since a point cloud has a larger capacity than 2D images, a technology to compress the point cloud is required, i.e., standardized in the international standard organization MPEG as a video-based point cloud compression (V-PCC). V-PCC decomposes 3D point cloud data into 2D patches along orthogonal directions, and those patches are placed into a 2D image sequence, and then compressed using existing 2D video codecs. However, data loss may occur while converting a 3D point cloud into a 2D image sequence and encoding this sequence using a legacy video codec. This data loss can cause deterioration in the quality of a reconstructed point cloud. This paper proposed a method of enhancing a reconstructed point cloud by applying a super resolution network to the 2D patch image sequence of a 3D point cloud.
引用
收藏
页码:425 / 442
页数:18
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