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Perceptually driven 3D distance metrics with application to watermarking

Abstract : This paper presents an objective structural distorsion measure which reflects the visual similarity between 3D meshes and thus can be used for quality assessment. The proposed tool is not linked to any specific application and thus can be used to evaluate any kinds of 3D mesh processing algorithms (simplification, compression, watermarking etc.). This measure follows the concept of structural similarity recently introduced for 2D image quality assessment by Wang \emph{et al.} \cite{WANG:2004} and is based on curvature analysis (mean, standard deviation, covariance) on local windows of the meshes. Evaluation and comparison with geometric metrics are done through a subjective experiment based on human evaluation of a set of distorted objects. A quantitative perceptual metric is also derived from the proposed structural distorsion measure, for the specific case of watermarking quality assessment, and is compared with recent state of the art algorithms. Both visual and quantitative results demonstrate the robustness of our approach and its strong correlation with subjective ratings.
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Submitted on : Monday, May 29, 2017 - 11:55:28 AM
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Guillaume Lavoué, Elisa Drelie Gelasca, Florent Dupont, Atilla Baskurt, Touradj Ebrahimi. Perceptually driven 3D distance metrics with application to watermarking. SPIE Applications of Digital Image Processing XXIX, Aug 2006, San Diego, United States. ⟨10.1117/12.686964⟩. ⟨hal-01528572⟩



Les métriques sont temporairement indisponibles