In computer graphics, rendering visually detailed scenes is often achieved through texturing. We propose a method for on-the-fly non-periodic infinite texturing of surfaces based on a single image. Pattern repetition is avoided by defining patches within each texture whose content can be changed at runtime. In addition, we consistently manage multi-scale using one input image per represented scale. Undersampling artifacts are avoided by accounting for fine-scale features while colors are transferred between scales. Eventually, we allow for relief-enhanced rendering and provide a tool for intuitive creation of height maps. This is done using an adhoc local descriptor that measures feature self-similarity in order to propagate height values provided by the user for a few selected texels only. Thanks to the patch-based system, manipulated data are compact and our texturing approach is easy to implement on GPU. The multi-scale extension is capable of rendering finely detailed textures in real-time.

Accurate refraction, thanks to raytracing, has always been a popular effect in computer graphics. However, devising a technique that produces realistic refractions at interactive rates remains an open problem.In this paper, a method to achieve realistic and interactive refractive effects through complex static geometry is proposed. It relies on an offline step where many light paths through the object are preevaluated. During rendering, these precomputed paths are used to provide approximations of actual refracted paths through the geometry, enabling further sampling of an environment map. The relevant information of the light paths, namely final output direction when leaving refractive object, is compressed using frequency domain based spherical harmonics. The matching decompression procedure, entirely offloaded onto graphics hardware, is handled at interactive speed.

Abstract-In this paper, we introduce a novel approach intended to simplify the production of multimedia content from real objects for the purpose of knowledge sharing, which is particularly appropriate to the cultural heritage field. It consists in a pipeline that covers all steps from the digitization of the objects up to the Web publishing of the resulting digital copies. During a first stage, the digitization is performed by a high speed 3D scanner that recovers the object's geometry. A second stage then extracts from the recovered data a color texture as well as a texture of details, in order to enrich the acquired geometry in a more realistic way. Finally, a third stage converts these data so that they are compatible with the recent WebGL paradigm, then providing 3D multimedia content directly exploitable by end-users by means of standard Internet browsers. The pipeline design is centered on automation and speed, so that it can be used by non expert users to produce multimedia content from potentially large object's collections, like it may be the case in cultural heritage. The choice of a high speed scanner is particularly adapted for such a design, since this kind of devices has the advantage of being fast and intuitive. Processing stages that follow the digitization are both completely automatic and "seamless", in the sense that it is not incumbent upon the user to perform tasks manually, nor to use external softwares that generally need additional operations to solve compatibility issues.

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parametric colour functions are widely used in Image-Based Rendering and Image Relighting. They make it possible to express the colour of a point depending on a continuous directional parameter: the viewing or the incident light direction. Producing such functions from acquired data is promising but difficult. Indeed, an intensive acquisition process resulting in dense and uniform sampling is not always possible. Conversely, a simpler acquisition process results in sparse, scattered and noisy data on which parametric functions can hardly be fitted without introducing artefacts. Within this context, we present two contributions. The first one is a robust least-squares-based method for fitting 2D parametric colour functions on sparse and scattered data. Our method works for any amount and distribution of acquired data, as well as for any function expressed as a linear combination of basis functions. We tested our fitting for both image-based rendering (surface light fields) and image relighting using polynomials and spherical harmonics. The second one is a statistical analysis to measure the robustness of any fitting method. This measure assesses a trade-off between precision of the fitting and stability with respect to input sampling conditions. This analysis along with visual results confirm that our fitting method is robust and reduces reconstruction artefacts for poorly sampled data while preserving the precision for a dense and uniform sampling.