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A perceptual quality metric for 3D triangle meshes based on spatial pooling

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Abstract

In computer graphics, various processing operations are applied to 3D triangle meshes and these processes often involve distortions, which affect the visual quality of surface geometry. In this context, perceptual quality assessment of 3D triangle meshes has become a crucial issue. In this paper, we propose a new objective quality metric for assessing the visual difference between a reference mesh and a corresponding distorted mesh. Our analysis indicates that the overall quality of a distorted mesh is sensitive to the distortion distribution. The proposed metric is based on a spatial pooling strategy and statistical descriptors of the distortion distribution. We generate a perceptual distortion map for vertices in the reference mesh while taking into account the visual masking effect of the human visual system. The proposed metric extracts statistical descriptors from the distortion map as the feature vector to represent the overall mesh quality. With the feature vector as input, we adopt a support vector regression model to predict the mesh quality score.We validate the performance of our method with three publicly available databases, and the comparison with state-of-the-art metrics demonstrates the superiority of our method. Experimental results show that our proposed method achieves a high correlation between objective assessment and subjective scores.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61373084, 61711530245), the Innovation Program of Shanghai Municipal Education Commission (14YZ011), and the Key Project of Shanghai Science and Technology Commission (17511106802).

Author information

Authors and Affiliations

  1. School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China

    Xiang Feng, Wanggen Wan, Haoyu Chen & Pengfei Li

  2. Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, 2007, Australia

    Xiang Feng & Richard Yi Da Xu

  3. Institute of Smart City, Shanghai University, Shanghai, 200444, China

    Xiang Feng, Wanggen Wan, Haoyu Chen & Pengfei Li

  4. Department of Computing, Electronics and Mechatronics, Universidad de las Américas Puebla (UDLAP), Cholula, 72820, Mexico

    J. Alfredo Sánchez

Authors
  1. Xiang Feng
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  2. Wanggen Wan
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  3. Richard Yi Da Xu
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  4. Haoyu Chen
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  5. Pengfei Li
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  6. J. Alfredo Sánchez
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Corresponding author

Correspondence to Xiang Feng.

Additional information

Xiang Feng received his BE degree from the School of Communication and Information Engineering, Shanghai University (SHU), China in 2011. He is now a dual PhD student in SHU and University of Technology Sydney (UTS),Australia. He is also a member of Institute of Smart City, SHU. He was awarded the CSC Scholarship (China Scholarship Council) to study at UTS between August 2014 and September 2015. His research interests include 3D modeling and reconstruction, 3D deformation and animation, and perceptual quality assessment.

Wanggen Wan is a professor of the School of Communication and Information Engineering, Shanghai University (SHU), China. He received his PhD Degree from Xidian University, China in 1992. He was Postdoctoral Research Fellow at the Information and Control Engineering Department of Xi’an Jiao-Tong University from 1993 to 1995. From 1995 to 1998, he was working at the Electronic and Information Engineering Department of SHU. He was a visiting scholar at the Electrical and Electronic Engineering Department of HKUST in 1998 and 1999. He was a visiting professor and section head at Multimedia Innovation Center of HKPU from 2000 to 2004. His research interests include computer graphics, signal processing, and data mining.

Richard Yi Da Xu is currently an associate professor of the School of Electrical and Data Engineering, University of Technology, Sydney (UTS), Australia. He received the BE degree in computer engineering from the University of New South Wales, Sydney, Australia in 2001, and PhD degree in computer sciences from the UTS in 2006. His current research interests include machine learning, computer vision, and statistical data mining.

Haoyu Chen is a postdoc of the School of Communication and Information Engineering, Shanghai University (SHU), China. He is also a member of Institute of Smart City, SHU. He received the PhD degree from the School of Information Systems, University of Southern Queensland (USQ), Australia in 2016. He was awarded the CSC Scholarship (China Scholarship Council) to study as a PhD student at USQ between October 2009 and November 2015. His research interests include perceptual quality assessment and audio signal processing.

Pengfei Li is a master student at the School of Communication and Information Engineering, Shanghai University, China. He received his BE degree from the School of Information and Electrical Engineering, Harbin Institute of Technology (Weihai), China in 2014. His research interests include 3D data compression and transmission and perceptual quality assessment.

J. Alfredo Sánchez is a professor of computer science and director of the Laboratory of Interactive and Cooperative Technologies at Universidad de las Américas Puebla (UDLAP), Mexico. He received his MS and PhD degrees in computer science from Texas A&M University, USA in 1993 and 1996, respectively. He chairs the Latin American Community of Human–Computer Interaction under ACM’s SIGCHI, and is co-founder of the Latin American Conference Series on Human–Computer Interaction (CLIHC). He also has served as president of the Mexican Computer Science Society and is a member of the National Researchers System. His research interests lie in the areas of human–computer interaction, natural user interfaces, and information visualization.

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Feng, X., Wan, W., Xu, R.Y.D. et al. A perceptual quality metric for 3D triangle meshes based on spatial pooling. Front. Comput. Sci. 12, 798–812 (2018). https://doi.org/10.1007/s11704-017-6328-x

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  • DOI: https://doi.org/10.1007/s11704-017-6328-x

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