JPEG Pleno Call for Proposals responses quality assessment
João P.C Prazeres (Universidade da Beira Interior); Zhe Luo (University of Technology Sydney); Antonio Pinheiro (U.B.I. & I.T.); Luis A da Silva Cruz (Dep. Electrical and Computer Engineering - Univ. of Coimbra); Stuart Perry (University of Technology Sydney)
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07 Jun 2023
In this paper, the quality evaluation of the responses to the Call for Proposals
(CfP) of JPEG Pleno Point Cloud Coding is presented. Three responses to the CfP were evaluated together with the state of the anchor codecs G-PCC and V-PCC from MPEG. The JPEG committee selected a set of eight point clouds that were encoded at different pre-established bitrates. For the subjective evaluation of the responses to the CfP, a set of video sequences were created where the reference and distorted decoded point clouds were rotated over their axis side by side.
Furthermore, the objective quality metrics PCQM, PSNR D1, PSNR D2, PSNR Y and PSNR YUV were computed, and compared with the subjective evaluation results. This study revealed that the deep learning solutions outperformed G-PCC but are still below the performance of V-PCC regarding color representation. PCQM showed the best performance in predicting the compression quality.
