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Volume: 34 | Article ID: 3DIA-225
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Quality analysis of point cloud coding solutions
  DOI :  10.2352/EI.2022.34.17.3DIA-225  Published OnlineJanuary 2022
Abstract
Abstract

In this paper, a subjective quality based comparison between four point clouds codecs is presented. For that, a set of six point clouds was chosen. They were coded with four different point cloud encoding solutions, notably the MPEG V-PCC and G-PCC, a deep learning coding solution RS-DLPCC and also Draco, with different bit rates. A subjective test where the distorted and reference point clouds were rotated in a video sequence side by side followed by the quality evaluation, was conducted. Then the performance of a set of four point cloud objective quality metrics of he quality, was analysed using the subjective quality evaluation results. These metrics are usually reported as providing a good representation and are often used to evaluate compression solutions. In fact, the studied metrics tend to provide a good representation for V-PCC and G-PCC, an acceptable representation for RS-DLPCC, and a bad representation for Draco. It was also concluded that V-PCC is the best codec of the studied ones. The deep learning based solution still performs worst than the two MPEG codecs.

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  Cite this article 

João Prazeres, Manuela Pereira, Antonio Pinheiro, "Quality analysis of point cloud coding solutionsin Proc. IS&T Int’l. Symp. on Electronic Imaging: 3D Imaging and Applications,  2022,  pp 225-1 - 225-6,  https://doi.org/10.2352/EI.2022.34.17.3DIA-225

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