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
相关论文
共 50 条
  • [21] Adaptive nonlinear filters for 2D and 3D image enhancement
    Guillon, S
    Baylou, P
    Najim, M
    Keskes, N
    SIGNAL PROCESSING, 1998, 67 (03) : 237 - 254
  • [22] Development of the generation tool of 3D contents from 2D image
    Niitsu, Y
    6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XX, PROCEEDINGS EXTENSION, 2002, : 57 - 60
  • [23] 3D Localization of a Mobile Robot by Using Monte Carlo Algorithm and 2D Features of 3D Point Cloud
    Vinicio Rosas-Cervantes
    Soon-Geul Lee
    International Journal of Control, Automation and Systems, 2020, 18 : 2955 - 2965
  • [24] 3D Localization of a Mobile Robot by Using Monte Carlo Algorithm and 2D Features of 3D Point Cloud
    Rosas-Cervantes, Vinicio
    Lee, Soon-Geul
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2020, 18 (11) : 2955 - 2965
  • [25] Fusion Render Cloud System for 3D Contents Using a Super Computer
    Choi, E-Jung
    Kim, Seoksoo
    SIGNAL PROCESSING AND MULTIMEDIA, 2010, 123 : 204 - 211
  • [26] Development of a Method for Detecting Cutting Points of Wilted Leaves Using 2D Image Keypoints and 3D Point Cloud
    Department of Mechanical Design and Robot Engineering, Seoul National University of Science and Technology, Korea, Republic of
    不详
    J. Inst. Control Rob. Syst., 2024, 11 (1237-1244): : 1237 - 1244
  • [27] Accurately 3D neuron localization using 2D conv-LSTM super-resolution segmentation network
    Zhou, Hang
    Li, Yuxin
    Wen, Wu
    Yang, Hao
    Ma, Yayu
    Chen, Min
    IET IMAGE PROCESSING, 2024, 18 (02) : 535 - 547
  • [28] 2D TO 3D LABEL PROPAGATION FOR OBJECT DETECTION IN POINT CLOUD
    Lertniphonphan, Kanokphan
    Komorita, Satoshi
    Tasaka, Kazuyuki
    Yanagihara, Hiromasa
    2018 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA & EXPO WORKSHOPS (ICMEW 2018), 2018,
  • [29] Face image super-resolution using 2D CCA
    An, Le
    Bhanu, Bir
    SIGNAL PROCESSING, 2014, 103 : 184 - 194
  • [30] Face image super-resolution using 2D CCA
    An, Le
    Bhanu, Bir
    Signal Processing, 2014, 103 : 184 - 194