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PCQD-AR: Subjective Quality Assessment of Compressed Point Clouds with Head-mounted Augmented Reality
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  • Chunling Fan,
  • Yun Zhang,
  • linwei Zhu,
  • Xinju Wu
Chunling Fan
Shenzhen Polytechnic
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Yun Zhang
Sun Yat-Sen University

Corresponding Author:[email protected]

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linwei Zhu
SIAT
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Xinju Wu
City University of Hong Kong
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Abstract

In this letter, the colored point cloud quality assessment in Augmented Reality (AR) environment was fully studied through subjective test. Firstly, we present a point cloud dataset, named Point Cloud Quality Dataset-AR (PCQD-AR), including ten reference point clouds and their 90 distorted versions, which were encoded by the reference software of Video-based Point Cloud Compression (V-PCC) under different pairs of geometry and texture quantization parameters. Then, the impact of geometry and texture distortions on perceived quality of point clouds in the AR environment was discussed in detail. Moreover, we evaluate the performance of existing objective point cloud quality assessment metrics on the proposed dataset. The subjective dataset including the values of Mean Opinion Score (MOS) will be released after acceptance.
18 Jul 2023Submitted to Electronics Letters
19 Jul 2023Assigned to Editor
19 Jul 2023Submission Checks Completed
04 Sep 2023Reviewer(s) Assigned