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

  • Cao, Chao
  • Preda, Marius
  • Zakharchenko, Vladyslav
  • Jang, Euee S.
  • Zaharia, Titus
Citations

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64
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81

초록

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.

키워드

Three-dimensional displaysImage color analysisOctreesTransform codingEncodingComputer graphicsImage codingCloud computingVideo compression3-D graphicscompressionmultimedia systemspoint cloudsrealistic modelingstandardsLOSSLESS COMPRESSIONALGORITHMROBUST
제목
Compression of Sparse and Dense Dynamic Point Clouds-Methods and Standards
저자
Cao, ChaoPreda, MariusZakharchenko, VladyslavJang, Euee S.Zaharia, Titus
DOI
10.1109/JPROC.2021.3085957
발행일
2021-09
유형
Article
저널명
Proceedings of the IEEE
109
9
페이지
1537 ~ 1558