Perception based heterogeneous subsurface scattering for film

Many real world materials exhibit complex subsurface scattering of light. This internal light interaction creates the perception of translucency for the human visual system. Translucent materials and simulation of the subsurface scattering of light has become an expected necessity for generating warmth and realism in computer generated imagery. The light transport within heterogenous materials, such as marble, has proved challenging to model and render. The current material models available to digital artists have been limited to homogeneous subsurface scattering despite a few publications documenting success at simulating heterogeneous light transport. While the publications successfully simulate this complex phenomenon, the material descriptions have been highly specialized and far from intuitive. By combining the measurable properties of heterogeneous translucent materials with the defining properties of translucency, as perceived by the human visual system, a description of heterogeneous translucent materials that is suitable for artist use in a film production pipeline can be achieved. Development of the material description focuses on integration with the film pipeline, ease of use, and reasonable approximation of heterogeneous translucency based on perception. Methods of material manipulation are explored to determine which properties should be modifiable by artists while maintaining the perception of heterogenous translucency

Exploration of Mouth Shading and Lighting in CG Production

The lighting and shading of human teeth in current computer animation features and live-action movies with effects are often intentionally avoided or processed by simple methods since they interact with light in complex ways through their intricate layered structure. The semi-translucent appearance of natural human teeth which result from subsurface scattering is difficult to replicate in synthetic scenes, though two techniques are often implemented. The first technique is to create an anatomically correct layered model, and render the teeth with both theoretically and empirically derived optical parameters of human teeth using physical subsurface materials. The second technique largely takes advantage of visual cheating, achieved by irradiance blending of finely painted textures. The result visually confirms that for most situations, non-physically based shading can yield believable rendered teeth by finely controlling contribution layers. In particular situations, such as an extremely close shot of a mouth, however, a physically correct shading model is necessary to produce highly translucent and realistic teeth

Procedural Generation and Rendering of Realistic, Navigable Forest Environments: An Open-Source Tool

Simulation of forest environments has applications from entertainment and art creation to commercial and scientific modelling. Due to the unique features and lighting in forests, a forest-specific simulator is desirable, however many current forest simulators are proprietary or highly tailored to a particular application. Here we review several areas of procedural generation and rendering specific to forest generation, and utilise this to create a generalised, open-source tool for generating and rendering interactive, realistic forest scenes. The system uses specialised L-systems to generate trees which are distributed using an ecosystem simulation algorithm. The resulting scene is rendered using a deferred rendering pipeline, a Blinn-Phong lighting model with real-time leaf transparency and post-processing lighting effects. The result is a system that achieves a balance between high natural realism and visual appeal, suitable for tasks including training computer vision algorithms for autonomous robots and visual media generation.Comment: 14 pages, 11 figures. Submitted to Computer Graphics Forum (CGF). The application and supporting configuration files can be found at https://github.com/callumnewlands/ForestGenerato

The Impact of Surface Normals on Appearance

The appearance of an object is the result of complex light interaction with the object. Beyond the basic interplay between incident light and the object\u27s material, a multitude of physical events occur between this illumination and the microgeometry at the point of incidence, and also beneath the surface. A given object, made as smooth and opaque as possible, will have a completely different appearance if either one of these attributes - amount of surface mesostructure (small-scale surface orientation) or translucency - is altered. Indeed, while they are not always readily perceptible, the small-scale features of an object are as important to its appearance as its material properties. Moreover, surface mesostructure and translucency are inextricably linked in an overall effect on appearance. In this dissertation, we present several studies examining the importance of surface mesostructure (small-scale surface orientation) and translucency on an object\u27s appearance. First, we present an empirical study that establishes how poorly a mesostructure estimation technique can perform when translucent objects are used as input. We investigate the two major factors in determining an object\u27s translucency: mean free path and scattering albedo. We exhaustively vary the settings of these parameters within realistic bounds, examining the subsequent blurring effect on the output of a common shape estimation technique, photometric stereo. Based on our findings, we identify a dramatic effect that the input of a translucent material has on the quality of the resultant estimated mesostructure. In the next project, we discuss an optimization technique for both refining estimated surface orientation of translucent objects and determining the reflectance characteristics of the underlying material. For a globally planar object, we use simulation and real measurements to show that the blurring effect on normals that was observed in the previous study can be recovered. The key to this is the observation that the normalization factor for recovered normals is proportional to the error on the accuracy of the blur kernel created from estimated translucency parameters. Finally, we frame the study of the impact of surface normals in a practical, image-based context. We discuss our low-overhead, editing tool for natural images that enables the user to edit surface mesostructure while the system automatically updates the appearance in the natural image. Because a single photograph captures an instant of the incredibly complex interaction of light and an object, there is a wealth of information to extract from a photograph. Given a photograph of an object in natural lighting, we allow mesostructure edits and infer any missing reflectance information in a realistically plausible way

Image-based Material Editing

Photo editing software allows digital images to be blurred, warped or re-colored at the touch of a button. However, it is not currently possible to change the material appearance of an object except by painstakingly painting over the appropriate pixels. Here we present a set of methods for automatically replacing one material with another, completely different material, starting with only a single high dynamic range image, and an alpha matte specifying the object. Our approach exploits the fact that human vision is surprisingly tolerant of certain (sometimes enormous) physical inaccuracies. Thus, it may be possible to produce a visually compelling illusion of material transformations, without fully reconstructing the lighting or geometry. We employ a range of algorithms depending on the target material. First, an approximate depth map is derived from the image intensities using bilateral filters. The resulting surface normals are then used to map data onto the surface of the object to specify its material appearance. To create transparent or translucent materials, the mapped data are derived from the object\u27s background. To create textured materials, the mapped data are a texture map. The surface normals can also be used to apply arbitrary bidirectional reflectance distribution functions to the surface, allowing us to simulate a wide range of materials. To facilitate the process of material editing, we generate the HDR image with a novel algorithm, that is robust against noise in individual exposures. This ensures that any noise, which would possibly have affected the shape recovery of the objects adversely, will be removed. We also present an algorithm to automatically generate alpha mattes. This algorithm requires as input two images--one where the object is in focus, and one where the background is in focus--and then automatically produces an approximate matte, indicating which pixels belong to the object. The result is then improved by a second algorithm to generate an accurate alpha matte, which can be given as input to our material editing techniques

Model for volume lighting and modeling

Journal ArticleAbstract-Direct volume rendering is a commonly used technique in visualization applications. Many of these applications require sophisticated shading models to capture subtle lighting effects and characteristics of volumetric data and materials. For many volumes, homogeneous regions pose problems for typical gradient-based surface shading. Many common objects and natural phenomena exhibit visual quality that cannot be captured using simple lighting models or cannot be solved at interactive rates using more sophisticated methods. We present a simple yet effective interactive shading model which captures volumetric light attenuation effects that incorporates volumetric shadows, an approximation to phase functions, an approximation to forward scattering, and chromatic attenuation that provides the subtle appearance of translucency. We also present a technique for volume displacement or perturbation that allows realistic interactive modeling of high frequency detail for both real and synthetic volumetric data

Hyperspectral Modeling of Material Appearance: General Framework, Challenges and Prospects

The main purpose of this tutorial is to address theoretical and practical issues involved in the development of predictive material appearancemodels for interdisciplinary applications within and outside the visible spectral domain. We examine the specific constraints and pitfalls found in each of the key stages of the model development framework, namely data collection, design and evaluation, and discuss alternatives to enhance the effectiveness of the entire process. Although predictive material appearance models developed by computer graphics researchers are usually aimed at realistic image synthesis applications, they also provide valuable support for a myriad of advanced investigations in related areas, such as computer vision, image processing and pattern recognition, which rely on the accurate analysis and interpretation of material appearance attributes in the hyperspectral domain. In fact, their scope of contributions goes beyond the realm of traditional computer science applications. For example, predictive light transport simulations, which are essential for the development of these models, are also regularly beingused by physical and life science researchers to understand andpredict material appearance changes prompted by mechanisms which cannot be fully studied using standard ``wet'' experimental procedures.For completeness, this tutorial also provides an overview of such synergistic research efforts and in silico investigations, which are illustrated by case studies involving the use of hyperspectral material appearance models