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Compression of Sparse and Dense Dynamic Point Clouds-Methods and Standards

Authors
Cao, ChaoPreda, MariusZakharchenko, VladyslavJang, Euee S.Zaharia, Titus
Issue Date
Sep-2021
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Three-dimensional displays; Image color analysis; Octrees; Transform coding; Encoding; Computer graphics; Image coding; Cloud computing; Video compression; 3-D graphics; compression; multimedia systems; point clouds; realistic modeling; standards
Citation
PROCEEDINGS OF THE IEEE, v.109, no.9, pp.1537 - 1558
Indexed
SCIE
SCOPUS
Journal Title
PROCEEDINGS OF THE IEEE
Volume
109
Number
9
Start Page
1537
End Page
1558
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/141128
DOI
10.1109/JPROC.2021.3085957
ISSN
0018-9219
Abstract
In this article, a survey of the point cloud compression (PCC) methods by organizing them with respect to the data structure, coding representation space, and prediction strategies is presented. Two paramount families of approaches reported in the literature-the projection- and octree-based methods-are proven to be efficient for encoding dense and sparse point clouds, respectively. These approaches are the pillars on which the Moving Picture Experts Group Committee developed two PCC standards published as final international standards in 2020 and early 2021, respectively, under the names: video-based PCC and geometry-based PCC. After surveying the current approaches for PCC, the technologies underlying the two standards are described in detail from an encoder perspective, providing guidance for potential standard implementors. In addition, experiment evaluations in terms of compression performances for both solutions are provided.
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Jang, Euee S.
COLLEGE OF ENGINEERING (SCHOOL OF COMPUTER SCIENCE)
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