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

PubDate: Aug 2020

Teams: Chinese Academy of Sciences；City University of Hong Kong

Writers: Xinju Wu, Yun Zhang, Chunling Fan, Junhui Hou, Sam Kwong

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

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 303 valid 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 impacts of contents and geometry and texture attributes are further discussed in this paper. Then, we evaluate our subjective database with current objective PCQA methods and propose an objective weighted projection-based method to improve the consistency between observers’ awareness and the importance of projected views. Our subjective database and findings can be used in perception-based point cloud processing, transmission, and coding, especially for Virtual Reality applications. The subjective dataset and quality scores will be available on the public repository.