Point cloud coding: A privileged view driven by a classification taxonomy
; Dricot, A.
Brites , C.
Signal Processing: Image Communication Vol. 85, Nº -, pp. - - -, July, 2020.
ISSN (print): 0923-5965
Scimago Journal Ranking: 0,54 (in 2020)
Digital Object Identifier: 10.1016/j.image.2020.115862
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Humans mainly communicate among them and with the world around them using light and vision, thus
implying that visual representation technologies play a central role in human societies. While visual
representation has been based on the 2D representation paradigm for many decades, multiple developments
are nowadays pressing towards the adoption of more realistic and immersive 3D visual representation models.
Point clouds are one of these emerging representation models. However, the huge amount of data involved
asks for highly efficient coding solutions, some of which have recently started to be developed by the MPEG
and JPEG standardization groups. In this hectic context, this paper proposes a privileged view over the current
point cloud coding technologies, driven by a novel, appropriate classification taxonomy. For this purpose, some
of the most representative point cloud coding solutions available in the literature will be reviewed to exercise
the most relevant classification paths in the proposed taxonomy. It is expected that this type of classification
taxonomy and privileged view may help better understanding the point cloud coding landscape for further
solid and consistent advancements in this emerging technical area.