2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSS-3DPC.1
Paper Title CMDM-VAC: IMPROVING A PERCEPTUAL QUALITY METRIC FOR 3D GRAPHICS BY INTEGRATING A VISUAL ATTENTION COMPLEXITY MEASURE
Authors Yana Nehmé, Laboratoire d’InfoRmatique en Image et Systèmes d’information (LIRIS CNRS), France; Mona Abid, Laboratoire des Sciences du Numérique de Nantes (LS2N CNRS), France; Guillaume Lavoué, Laboratoire d’InfoRmatique en Image et Systèmes d’information (LIRIS CNRS), France; Matthieu Perreira Da Silva, Patrick Le Callet, Laboratoire des Sciences du Numérique de Nantes (LS2N CNRS), France
SessionSS-3DPC: Special Session: Coding and quality assessment of 3D point clouds
LocationArea A
Session Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Poster
Topic Special Sessions: Recent Advances in Coding and Quality Assessment of 3D Point Clouds
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Abstract Many objective quality metrics have been proposed over the years to automate the task of subjective quality assessment. However, few of them are designed for 3D graphical contents with appearance attributes; existing ones are based on geometry and color measures, yet they ignore the visual saliency of the objects. In this paper, we combined an optimal subset of geometry-based and color-based features, provided by a state-of-the-art quality metric for 3D colored meshes, with a visual attention complexity feature adapted to 3D graphics. The performance of our proposed new metric is evaluated on a dataset of 80 meshes with diffuse colors, generated from 5 source models corrupted by commonly used geometry and color distortions. With our proposed metric, we showed that the use of the attentional complexity feature brings a significant gain in performance and better stability.