Learning quadrangulated patches for 3D shape parameterization and completion

We propose a novel 3D shape parameterization by surface patches, that are oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail on local patches, we learn a patch dictionary that identifies principal surface features of the shape. Unlike previous methods, we are able to encode surface patches of variable size as determined by the user. We propose novel methods for dictionary learning and patch reconstruction based on the query of a noisy input patch with holes. We evaluate the patch dictionary towards various applications in 3D shape inpainting, denoising and compression. Our method is able to predict missing vertices and inpaint moderately sized holes. We demonstrate a complete pipeline for reconstructing the 3D mesh from the patch encoding. We validate our shape parameterization and reconstruction methods on both synthetic shapes and real world scans. We show that our patch dictionary performs successful shape completion of complicated surface textures.Comment: To be presented at International Conference on 3D Vision 2017, 201

Transfer of albedo and local depth variation to photo-textures

Acquisition of displacement and albedo maps for full building façades is a difficult problem and traditionally achieved through a labor intensive artistic process. In this paper, we present a material appearance transfer method, Transfer by Analogy, designed to infer surface detail and diffuse reflectance for textured surfaces like the present in building façades. We begin by acquiring small exemplars (displacement and albedo maps), in accessible areas, where capture conditions can be controlled. We then transfer these properties to a complete phototexture constructed from reference images and captured under diffuse daylight illumination. Our approach allows super-resolution inference of albedo and displacement from information in the photo-texture. When transferring appearance from multiple exemplars to façades containing multiple materials, our approach also sidesteps the need for segmentation. We show how we use these methods to create relightable models with a high degree of texture detail, reproducing the visually rich self-shadowing effects that would normally be difficult to capture using just simple consumer equipment. Copyright © 2012 by the Association for Computing Machinery, Inc

Livrable D2.2 of the PERSEE project : Analyse/Synthese de Texture

Livrable D2.2 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D2.2 du projet. Son titre : Analyse/Synthese de Textur

Real-time transition texture synthesis for terrains.

Depicting the transitions where differing material textures meet on a terrain surface presents a particularly unique set of challenges in the field of real-time rendering. Natural landscapes are inherently irregular and composed of complex interactions between many different material types of effectively endless detail and variation. Although consumer grade graphics hardware is becoming ever increasingly powerful with each successive generation, terrain texturing remains a trade-off between realism and the computational resources available. Technological constraints aside, there is still the challenge of generating the texture resources to represent terrain surfaces which can often span many hundreds or even thousands of square kilometres. To produce such textures by hand is often impractical when operating on a restricted budget of time and funding. This thesis presents two novel algorithms for generating texture transitions in realtime using automated processes. The first algorithm, Feature-Based Probability Blending (FBPB), automates the task of generating transitions between material textures containing salient features. As such features protrude through the terrain surface FBPB ensures that the topography of these features is maintained at transitions in a realistic manner. The transitions themselves are generated using a probabilistic process that also dynamically adds wear and tear to introduce high frequency detail and irregularity at the transition contour. The second algorithm, Dynamic Patch Transitions (DPT), extends FBPB by applying the probabilistic transition approach to material textures that contain no salient features. By breaking up texture space into a series of layered patches that are either rendered or discarded on a probabilistic basis, the contour of the transition is greatly increased in resolution and irregularity. When used in conjunction with high frequency detail techniques, such as alpha masking, DPT is capable of producing endless, detailed, irregular transitions without the need for artistic input