Espaces de la citoyenneté en Amérique latine

Contents

List of figures ixI General Introduction and Notions of Digital Shape Processing11 General Introduction 31.1 Context of the work . . . . . . . . . . . . . . . . . . . . . . . . 31.2 Organization of the thesis . . . . . . . . . . . . . . . . . . . . 62 Digital Shape Processing 92.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.2 Shapes and their digital representations . . . . . . . . . . . . 92.2.1 Non-Uniform Rational B-Splines (NURBS) . . . . . . 102.2.2 3D triangle meshes . . . . . . . . . . . . . . . . . . . . 112.3 Digital Topology . . . . . . . . . . . . . . . . . . . . . . . . . . 132.4 Parameterization . . . . . . . . . . . . . . . . . . . . . . . . . 142.4.1 Digital parameterization . . . . . . . . . . . . . . . . . 162.4.2 Distortion energy estimation . . . . . . . . . . . . . . 162.4.3 Tutte parameterization . . . . . . . . . . . . . . . . . . 182.4.4 Conformal and harmonic parameterizations . . . . . 182.4.5 Authalic parameterization . . . . . . . . . . . . . . . . 192.5 Differential Geometry . . . . . . . . . . . . . . . . . . . . . . 202.6 Geodesic distances . . . . . . . . . . . . . . . . . . . . . . . . 252.7 Spectral Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 262.8 Multiresolution Analysis . . . . . . . . . . . . . . . . . . . . . 272.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30iv CONTENTSII Shape Perception 313 Perception of a 3D Shape 333.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333.2 Visualization Techniques . . . . . . . . . . . . . . . . . . . . . 343.2.1 Rendering . . . . . . . . . . . . . . . . . . . . . . . . . 343.2.2 Lighting Models . . . . . . . . . . . . . . . . . . . . . 353.2.3 Textures . . . . . . . . . . . . . . . . . . . . . . . . . . 393.2.4 Global Illumination . . . . . . . . . . . . . . . . . . . . 403.2.5 Non-Photorealistic Rendering (NPR) . . . . . . . . . . 413.2.6 Level of Detail . . . . . . . . . . . . . . . . . . . . . . . 423.3 Three-Dimensional Distance Metrics . . . . . . . . . . . . . . 433.3.1 Hausdorff distance . . . . . . . . . . . . . . . . . . . . 443.3.2 Volume based metric . . . . . . . . . . . . . . . . . . . 443.3.3 Quadric Error Measure . . . . . . . . . . . . . . . . . 453.3.4 Curvature Based Distance . . . . . . . . . . . . . . . . 453.3.5 RMSE, VSNR and Geometric Laplacian . . . . . . . . 453.3.6 Image-based metrics . . . . . . . . . . . . . . . . . . . 463.3.7 Perceptive models . . . . . . . . . . . . . . . . . . . . 463.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Shape Quality Assessment for 3D Watermarking Attacks 494.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494.2 Visual similarity metric through 2D projections . . . . . . . . 504.2.1 Mutual information . . . . . . . . . . . . . . . . . . . 504.2.2 Generating 2D views . . . . . . . . . . . . . . . . . . . 514.3 Subjective evaluation experiment . . . . . . . . . . . . . . . . 534.3.1 Experiment script . . . . . . . . . . . . . . . . . . . . . 554.3.2 Statistical Analysis of the Experimental Results . . . 564.4 Validation of the proposed metric . . . . . . . . . . . . . . . . 604.4.1 Noise addition . . . . . . . . . . . . . . . . . . . . . . 614.4.2 Vertex simplification . . . . . . . . . . . . . . . . . . . 624.4.3 Smoothing . . . . . . . . . . . . . . . . . . . . . . . . . 624.4.4 Image-based metrics and view variance . . . . . . . . 634.4.5 Final observations . . . . . . . . . . . . . . . . . . . . 644.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65CONTENTS vIII Towards 3D ShapeWatermarking 695 Introduction to Digital Watermarking 715.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 715.2 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 725.3 Applications of watermarking . . . . . . . . . . . . . . . . . . 755.3.1 Copy protection . . . . . . . . . . . . . . . . . . . . . . 755.3.2 Copyright protection . . . . . . . . . . . . . . . . . . . 765.3.3 Integrity protection . . . . . . . . . . . . . . . . . . . . 765.3.4 Self-indexed contents . . . . . . . . . . . . . . . . . . . 765.3.5 Augmented contents . . . . . . . . . . . . . . . . . . . 775.3.6 Steganography . . . . . . . . . . . . . . . . . . . . . . 775.3.7 Fingerprinting . . . . . . . . . . . . . . . . . . . . . . . 775.4 Watermarking of 3D Data . . . . . . . . . . . . . . . . . . . . 785.4.1 Why should 3D graphics content be protected? . . . . 785.4.2 Are there alternatives to 3D watermarking? . . . . . . 795.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 826 Survey of 3D DigitalWatermarking: From 3D Mesh Data Hidingtowards 3D Shape Blind and Robust Watermarking 836.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 846.2 3D Watermarking Applications and Requirements . . . . . . 856.2.1 3D Watermarking Applications . . . . . . . . . . . . . 856.2.2 Robustness and Attacks . . . . . . . . . . . . . . . . . 856.2.3 Imperceptibility . . . . . . . . . . . . . . . . . . . . . . 876.2.4 Capacity, Content and Security . . . . . . . . . . . . . 896.2.5 3D Watermarking Schemes Requirements . . . . . . . 906.3 3D Watermarking Schemes . . . . . . . . . . . . . . . . . . . 916.3.1 Spatial Domain . . . . . . . . . . . . . . . . . . . . . . 916.3.2 Transform Domain . . . . . . . . . . . . . . . . . . . . 1006.3.3 Compression Domain . . . . . . . . . . . . . . . . . . 1056.3.4 Attribute Domain . . . . . . . . . . . . . . . . . . . . . 1056.3.5 3D embedding and 2D retrieval . . . . . . . . . . . . . 1066.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1067 Spectral Watermarking of 3D meshes 1097.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1097.2 Spectral decomposition . . . . . . . . . . . . . . . . . . . . . . 1107.2.1 Discrete Laplacian Operator . . . . . . . . . . . . . . . 110vi CONTENTS7.2.2 Discrete Laplacian operators and the Principal Component Analysis . . . . . . . . . . . . . . . . . . . . . . 1127.2.3 Discrete Laplacian operators as connectivity-preserving linear mesh system . . . . . . . . . . . . . . . . . . . . 1137.2.4 Properties of discrete combinatorial mesh Laplacian operators . . . . . . . . . . . . . . . . . . . . . . . . . . 1157.2.5 Mesh spectra . . . . . . . . . . . . . . . . . . . . . . . 1177.3 Fixed basis decomposition, partitioning and overlapping . . 1187.3.1 Tutte projection . . . . . . . . . . . . . . . . . . . . . . 1207.3.2 Vertex mapping . . . . . . . . . . . . . . . . . . . . . . 1207.3.3 Partitioning and patch augmentation by overlapping 1227.4 Mesh geometry compression and progressive transmission . 1247.4.1 Visual metric . . . . . . . . . . . . . . . . . . . . . . . 1257.4.2 Geometric compression . . . . . . . . . . . . . . . . . 1267.4.3 Progressive transmission . . . . . . . . . . . . . . . . 1277.5 Watermarking . . . . . . . . . . . . . . . . . . . . . . . . . . . 1287.5.1 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . 1287.5.2 Results and discussion . . . . . . . . . . . . . . . . . . 1307.6 Conclusion, limitations and future work . . . . . . . . . . . . 1348 Re-Synchronization of Spectral Watermarks by Umbilical Points1378.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1378.2 Feature Points . . . . . . . . . . . . . . . . . . . . . . . . . . . 1388.2.1 Umbilical Points . . . . . . . . . . . . . . . . . . . . . 1398.2.2 Curvature Tensor Estimation . . . . . . . . . . . . . . 1408.2.3 Curvature Tensor Field Filtering and Topological Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 1418.2.4 Multi-Scale Analysis and Robust Umbilical Points . . 1508.2.5 Analogy with the Scale-Invariant Feature Transform 1518.3 Partition And Remeshing . . . . . . . . . . . . . . . . . . . . 1528.3.1 Sampling Independent Wavefronts . . . . . . . . . . . 1528.3.2 Building The Geodesic Delaunay Triangulation . . . 1538.3.3 Remeshing . . . . . . . . . . . . . . . . . . . . . . . . . 1548.4 Watermarking Encoding And Decoding . . . . . . . . . . . . 1558.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1568.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1599 3D Blind Local Watermarking and Robustness to Resampling and Cropping Attacks 1619.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161CONTENTS vii9.2 Overview of the proposed scheme . . . . . . . . . . . . . . . 1639.3 Robust Prongs Detection . . . . . . . . . . . . . . . . . . . . . 1659.3.1 Protrusion Function . . . . . . . . . . . . . . . . . . . 1659.3.2 Geodesics . . . . . . . . . . . . . . . . . . . . . . . . . 1669.3.3 Detecting Local Maxima . . . . . . . . . . . . . . . . . 1679.3.4 Computational Cost Optimization . . . . . . . . . . . 1699.4 Robust Local Neighborhoods . . . . . . . . . . . . . . . . . . 1709.5 Patch Radial Watermarking . . . . . . . . . . . . . . . . . . . 1729.5.1 Robust Center of Gravity Estimation . . . . . . . . . . 1739.5.2 Shape Histogram . . . . . . . . . . . . . . . . . . . . . 1749.5.3 Watermark Embedding . . . . . . . . . . . . . . . . . 1769.5.4 Watermark Decoding . . . . . . . . . . . . . . . . . . . 1789.6 Robustness Experimental Results . . . . . . . . . . . . . . . . 1799.6.1 Robustness of Prong Detection . . . . . . . . . . . . . 1799.6.2 Robustness of the Watermarking Scheme . . . . . . . 1799.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18010 Conclusion 18310.1 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 18310.1.1 Perceptual metric . . . . . . . . . . . . . . . . . . . . . 18410.1.2 Blind semi-fragile watermarking scheme based on spectral decomposition . . . . . . . . . . . . . . . . . 18410.1.3 Blind watermarking scheme robust against resampling18510.1.4 Blind watermarking scheme robust against resampling and cropping . . . . . . . . . . . . . . . . . . . . 18510.1.5 Related Applications . . . . . . . . . . . . . . . . . . . 18610.2 Lines of Future Work . . . . . . . . . . . . . . . . . . . . . . . 186Bibliography 189