Subjective Quality Database and Objective Study of Compressed Point Clouds with 6DoF Head-mounted Display

Xinju WU; Yun ZHANG; Chunling FAN; Junhui HOU; Sam KWONG

doi:10.1109/TCSVT.2021.3101484

Subjective Quality Database and Objective Study of Compressed Point Clouds with 6DoF Head-mounted Display

Xinju WU, Yun ZHANG, Chunling FAN, Junhui HOU, Sam KWONG

Research output: Journal Publications › Journal Article (refereed) › peer-review

42 Citations (Scopus)

Abstract

In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in compression distortion. Using a Head-Mounted Display (HMD) with six degrees of freedom, we establish a subjective PCQA database, named SIAT Point Cloud Quality Database (SIAT-PCQD). Our database consists of 340 distorted point clouds compressed by the MPEG point cloud encoder with the combination of 20 sequences and 17 pairs of geometry and texture quantization parameters. The impact of distorted geometry and texture attributes is further discussed in this paper. Then, we propose two projection-based objective quality evaluation methods, i.e., a weighted view projection based model and a patch projection based model. Our subjective database and findings can be used in point cloud processing, transmission, and coding, especially for virtual reality applications. The subjective dataset1 2 has been released in the public repository.

Original language	English
Pages (from-to)	4630-4644
Number of pages	15
Journal	IEEE Transactions on Circuits and Systems for Video Technology
Volume	31
Issue number	12
Early online date	30 Jul 2021
DOIs	https://doi.org/10.1109/TCSVT.2021.3101484
Publication status	Published - Dec 2021
Externally published	Yes

Bibliographical note

This work was supported in part by Guangdong International Science and Technology Cooperative Research Project under Grant 2018A050506063, in part by Shenzhen Science and Technology Program under Grant JCYJ20180507183823045 and Grant JCYJ20200109110410133, and in part by the Membership of Youth Innovation Promotion Association, Chinese Academy of Sciences under Grant 2018392.

Keywords

Point clouds
quality metrics
six degrees of freedom (6DoF)
subjective quality assessment
virtual reality

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10.1109/TCSVT.2021.3101484

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abstract = "In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in compression distortion. Using a Head-Mounted Display (HMD) with six degrees of freedom, we establish a subjective PCQA database, named SIAT Point Cloud Quality Database (SIAT-PCQD). Our database consists of 340 distorted point clouds compressed by the MPEG point cloud encoder with the combination of 20 sequences and 17 pairs of geometry and texture quantization parameters. The impact of distorted geometry and texture attributes is further discussed in this paper. Then, we propose two projection-based objective quality evaluation methods, i.e., a weighted view projection based model and a patch projection based model. Our subjective database and findings can be used in point cloud processing, transmission, and coding, especially for virtual reality applications. The subjective dataset1 2 has been released in the public repository.",

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AU - KWONG, Sam

N1 - This work was supported in part by Guangdong International Science and Technology Cooperative Research Project under Grant 2018A050506063, in part by Shenzhen Science and Technology Program under Grant JCYJ20180507183823045 and Grant JCYJ20200109110410133, and in part by the Membership of Youth Innovation Promotion Association, Chinese Academy of Sciences under Grant 2018392.

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N2 - In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in compression distortion. Using a Head-Mounted Display (HMD) with six degrees of freedom, we establish a subjective PCQA database, named SIAT Point Cloud Quality Database (SIAT-PCQD). Our database consists of 340 distorted point clouds compressed by the MPEG point cloud encoder with the combination of 20 sequences and 17 pairs of geometry and texture quantization parameters. The impact of distorted geometry and texture attributes is further discussed in this paper. Then, we propose two projection-based objective quality evaluation methods, i.e., a weighted view projection based model and a patch projection based model. Our subjective database and findings can be used in point cloud processing, transmission, and coding, especially for virtual reality applications. The subjective dataset1 2 has been released in the public repository.

AB - In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in compression distortion. Using a Head-Mounted Display (HMD) with six degrees of freedom, we establish a subjective PCQA database, named SIAT Point Cloud Quality Database (SIAT-PCQD). Our database consists of 340 distorted point clouds compressed by the MPEG point cloud encoder with the combination of 20 sequences and 17 pairs of geometry and texture quantization parameters. The impact of distorted geometry and texture attributes is further discussed in this paper. Then, we propose two projection-based objective quality evaluation methods, i.e., a weighted view projection based model and a patch projection based model. Our subjective database and findings can be used in point cloud processing, transmission, and coding, especially for virtual reality applications. The subjective dataset1 2 has been released in the public repository.

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KW - virtual reality

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Subjective Quality Database and Objective Study of Compressed Point Clouds with 6DoF Head-mounted Display

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