An Image-based Model for 3D Shape Quality Measure

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dc.contributor.authorAlhamazani, Fahden_US
dc.contributor.authorRosin, Paul L.en_US
dc.contributor.authorLai, Yu-Kunen_US
dc.contributor.editorVangorp, Peteren_US
dc.contributor.editorHunter, Daviden_US
dc.date.accessioned2023-09-12T05:44:45Z
dc.date.available2023-09-12T05:44:45Z
dc.date.issued2023
dc.description.abstractIn light of increased research on 3D shapes and the increased processing capability of GPUs, there has been a significant increase in available 3D applications. In many applications, assessment of perceptual quality of 3D shapes is required. Due to the nature of 3D representation, this quality assessment may take various forms. While it is straightforward to measure geometric distortions directly on the 3D shape geometry, such measures are often inconsistent with human perception of quality. In most cases, human viewers tend to perceive 3D shapes from their 2D renderings. It is therefore plausible to measure shape quality using their 2D renderings. In this paper, we present an image-based quality metric for evaluating 3D shape quality given the original and distorted shapes. To provide a good coverage of 3D geometry from different views, we render each shape from 12 equally spaced views, along with a variety of rendering styles to capture different aspects of visual characteristics. Image-based metrics such as SSIM (Structure Similarity Index Measure) are then used to measure the quality of 3D shapes. Our experiments show that by effectively selecting a suitable combination of rendering styles and building a neural network based model, we achieve significantly better prediction for subjective perceptual quality than existing methods.en_US
dc.description.sectionheadersShape Representation and Analysis
dc.description.seriesinformationComputer Graphics and Visual Computing (CGVC)
dc.identifier.doi10.2312/cgvc.20231187
dc.identifier.isbn978-3-03868-231-8
dc.identifier.pages19-27
dc.identifier.pages9 pages
dc.identifier.urihttps://doi.org/10.2312/cgvc.20231187
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/cgvc20231187
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Shape analysis
dc.subjectComputing methodologies
dc.subjectShape analysis
dc.titleAn Image-based Model for 3D Shape Quality Measureen_US
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