Guillaume Lavoué Introduction

• Guillaume Lavoué

Introduction

• Introduction

• The proposed roughness measure

• Results and application to masking

• Integration to compression / watermarking

Introduction

• Introduction

• The proposed roughness measure

• Results and application to masking

• Integration to compression / watermarking

The 3D corpus

• The 3D corpus

• 4 objects
• 6 versions : 3 noise strengths on smooth and rough areas

• Evaluation protocol

• 6 degraded versions are displayed to the observer together with the original object
• He must provide a score between 4 (identical to the original) and 0 (worst case)

• Results

Introduction

• Introduction

• The proposed roughness measure

• Results and application to masking

• Integration to compression / watermarking

Connectivity coding

• Connectivity coding

• Face Fixer [Isenburg and Snoeyink 2001]

• Geometry coding

• Simple differential coding
• Variable quantization: lower for rough region, higher for smooth ones

• Arithmetic coding

• Roughness classification

• Markov based clustering [Lavoué and Wolf 2008]

The Ohbuchi et al. [2002] non blind scheme:

• The Ohbuchi et al. [2002] non blind scheme:

• Mesh segmentation into patches
• Spectral decomposition of each patch
• Modulation of spectral coefficients (fixed strength α)
• Non blind extraction

Un algorithme de caractérisation de la rugosité de la surface

• Un algorithme de caractérisation de la rugosité de la surface

• Mise en évidence du phénomène de Masking par une expérience subjective

• Résultats encourageants après intégration pour la compression et le tatouage

• Pour + d’info:

• Lavoué, G. 2009. A local roughness measure for 3D meshes and its application to visual masking. ACM Trans. Appl. Percept. 5, 4 (Jan. 2009), 1-23.

• Et maintenant : Caractérisation plus théorique du phénomène par des expériences subjectives plus poussées