Perceptually driven 3D distance metrics with application to watermarking

This paper presents an objective structural distortion 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 et al.1 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 distortion 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.

[1]  S. Kanai,et al.  Digital Watermarking for 3D Polygons using Multiresolution Wavelet Decomposition , 1998 .

[2]  Sun-Jeong Kim,et al.  Discrete differential error metric for surface simplification , 2002, 10th Pacific Conference on Computer Graphics and Applications, 2002. Proceedings..

[3]  Oliver Benedens Watermarking of 3D-polygon-based models with robustness against mesh simplification , 1999, Electronic Imaging.

[4]  Mathieu De Craene,et al.  Three-dimensional image quality measurement for the benchmarking of 3D watermarking schemes , 2005, IS&T/SPIE Electronic Imaging.

[5]  Donald P. Greenberg,et al.  A model of visual masking for computer graphics , 1997, SIGGRAPH.

[6]  Paolo Cignoni,et al.  Metro: Measuring Error on Simplified Surfaces , 1998, Comput. Graph. Forum.

[7]  Martin Reddy,et al.  Perceptually Optimized 3D Graphics , 2001, IEEE Computer Graphics and Applications.

[8]  Gabriel Taubin,et al.  A signal processing approach to fair surface design , 1995, SIGGRAPH.

[9]  Scott J. Daly,et al.  Visible differences predictor: an algorithm for the assessment of image fidelity , 1992, Electronic Imaging.

[10]  Fabio Pellacini,et al.  Perceptually-driven decision theory for interactive realistic rendering , 2003, TOGS.

[11]  Benjamin Watson,et al.  Measuring and predicting visual fidelity , 2001, SIGGRAPH.

[12]  Touradj Ebrahimi,et al.  MESH: measuring errors between surfaces using the Hausdorff distance , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[13]  O'SullivanCarol,et al.  Predicting and Evaluating Saliency for Simplified Polygonal Models , 2005 .

[14]  Andrew P. Bradley,et al.  Perceptual quality metrics applied to still image compression , 1998, Signal Process..

[15]  Gary W. Meyer,et al.  A perceptually based adaptive sampling algorithm , 1998, SIGGRAPH.

[16]  Touradj Ebrahimi,et al.  Objective evaluation of the perceptual quality of 3D watermarking , 2005, IEEE International Conference on Image Processing 2005.

[17]  Oliver Benedens Two high capacity methods for embedding public watermarks into 3 D polygonal models , 1999 .

[18]  Carol O'Sullivan,et al.  Predicting and Evaluating Saliency for Simplified Polygonal Models , 2005, TAP.

[19]  Craig Gotsman,et al.  Spectral compression of mesh geometry , 2000, EuroCG.

[20]  Touradj Ebrahimi,et al.  A Multi-Scale Roughness Metric for 3D Watermarking Quality Assessment , 2005 .

[21]  Stefan Winkler,et al.  Perceptual blur and ringing metrics: application to JPEG2000 , 2004, Signal Process. Image Commun..

[22]  David W. Jacobs,et al.  Mesh saliency , 2005, ACM Trans. Graph..

[23]  Pierre Alliez,et al.  Anisotropic polygonal remeshing , 2003, ACM Trans. Graph..

[24]  David Cohen-Steiner,et al.  Restricted delaunay triangulations and normal cycle , 2003, SCG '03.

[25]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[26]  Irene Cheng,et al.  Quality metric for approximating subjective evaluation of 3-D objects , 2005, IEEE Transactions on Multimedia.

[27]  David W. Jacobs,et al.  Mesh saliency , 2005, SIGGRAPH 2005.

[28]  Ghassan Al-Regib,et al.  FQM: a fast quality measure for efficient transmission of textured 3D models , 2004, MULTIMEDIA '04.