The rapid proliferation of 3D volume data, including MRI and CT scans, is prompting the search within computer graphics for more effective volume visualisation techniques. Partially because of the traditional association with medical subjects, concepts borrowed from the domain of scientific illustration show great promise for enriching volume visualisation. This thesis describes the first general system dedicated to creating user-directed, variable-detail, scientific illustrations directly from volume data. In particular, using volume segmentation for explicit abstraction in non-photorealistic volume renderings is a new concept. The unique challenges and opportunities of volume data require rethinking many non-photorealistic algorithms that traditionally operate on polygonal meshes. The resulting 2D images are qualitatively different from but complementary to those normally seen in computer graphics, and inspire an analysis of the various artistic implications of volume models for scientific illustration.

The bidirectional reflectance distribution function has a four dimensional parameter space and such high dimensionality makes it impractical to use it directly in hardware rendering. When a BRDF has no analytical representation, common solutions to overcome this problem include expressing it as a sum of basis functions or factorizing it into several functions of smaller dimensions. This thesis describes factorization extensions that significantly improve factor computation speed and eliminate drawbacks of previous techniques that overemphasize low sample values. The improved algorithm is used to calculate factorizations and material maps from colored images. The technique presented in this thesis allows interactive definition of arbitrary materials, and although this method is based on physical parameters, it can be also used for achieving a variety of non-photorealistic effects.

This thesis describes two new techniques for enhancing the rendering quality of cartoon characters in toon-shading applications. The proposed methods can be used to improve the output quality of current cel shaders. The first technique which uses 2D image-based algorithms, enhances the silhouettes of the input geometry and reduces the computer generated artefacts. The silhouettes are found by using the Sobel filter and reconstructed by Bezier curve fitting. The intensity of the reconstructed silhouettes is then modified to create a stylised appearance. In the second technique, a new hair model based on billboarded particles is introduced. This method is found to be particularly useful for generating toon-like specular highlights for hair, which are important in cartoon animations. The whole rendering framework is implemented in C++ using the OpenGL API. OpenGL extensions and GPU programming are used to take the advantage of the functionalities of currently available graphics hardware. The programming of graphics hardware is done using Cg, a high level shader language.

With the push to exascale, in situ visualization and analysis will play an increasingly important role in high performance computing. Tightly coupling in situ visualization with simulations constrains resources for both, and these constraints force a complex balance of trade-offs. A performance model that provides an a priori answer for the cost of using an in situ approach for a given task would assist in managing the trade-offs between simulation and visualization resources. In this work, we present new statistical performance models, based on algorithmic complexity, that accurately predict the run-time cost of a set of representative rendering algorithms, an essential in situ visualization task. To train and validate the models, we create data-parallel rendering algorithms within a light-weight in situ infrastructure, and we conduct a performance study of an MPI+X rendering infrastructure used in situ with three HPC simulation applications. We then explore feasibility issues using the model for selected in situ rendering questions.

Emission nebulae are some of the most beautiful stellar phenomena. The newly formed hot stars inside the nebulae ionize the surrounding gas making it glow in variety of colors. The focus of this work is to find a method for interactive rendering of simulated emission nebulae. A rendering program has been developed to render and generate nebulae. The emission light color is evaluated as a function of the accumulated density between the gas and the ionizing star. The rendering program can render a large variety of nebulae from any viewpoint with interactive performance on PC hardware. The method proposed in this work is visually accurate to real nebulae.

No description available.

Call number: LD2668 .T4 1958 D85 / Master of Science

In this research, we study image composition in the context of computer rendering, investigate why composition is difficult with conventional rendering methods, and propose our solutions. Image composition is a process in which an artist improves a visual image to achieve certain aesthetic goals, and it is a central topic in studies of visual arts. Approaching the compositional quality of hand-made art work with computer rendering is a challenging task; but there is scarcely any in-depth research on this task from an interdisciplinary viewpoint between computer graphics and visual arts. Although recent developments of computer rendering have enabled the synthesis of high quality photographic images, most rendering methods only simulate a photographic process and do not permit straightforward compositional editing in the image space. In order to improve the visual quality of the digitally synthesized images, the knowledge of visual composition needs to be incorporated. This objective not only asks for novel algorithmic inventions, but also involves research in visual perception, painting, photography and other disciplines of visual arts. With examples from historical painting and contemporary photography, we inquire why and how a well-composed image elicits an aesthetic visual response from its viewer. Our analysis based on visual perception shows that the composition of an image serves as a guideline for the viewing process of that image; the composition of an image conveys an artist's intention of how the depicted scene should be viewed, and directs a viewer's eyes. A key observation is that for a composition to take effect, a viewer must be allowed to attentively look at the image for a period of time. From this analysis, we outline a few rules for composing light and shade in computer rendering, which serve as guidelines for designing rendering methods that create imagery beyond photorealistic depictions. Our original analysis elucidates the mechanism and function of image composition in the context of rendering, and offers clearly defined directions for algorithmic design. Theories about composition mostly remain in the literature of art critique and art history, while there are hardly any investigations on this topic in a technical context. Our novel analysis is an instructive contribution for enhancing the aesthetic quality of digitally synthesized images. We present two research projects that develop our analysis into rendering programs. We first show an interpolative material model, in which the surface shading is interpolated from input textures with a brightness value. The resultant rendering depicts surface brightness instead of light energy in the depicted scene. We also show a painting interface with this material model, with which an artist can directly compose surface brightness with a digital pen. In the second project, we ask an artist to provide a sketch of lighting design with coarse paint strokes on top of a rendering, while details of the light and shade in the depicted scene are automatically filled in by our program. This project is staged in the context of creating the visual effects of foliage shadows under sunshine. Our software tool also includes a novel method for generating coherent animations that resemble the movements of tree foliage in a gentle breeze. These programming projects validate the rendering methodology proposed by our theoretical analysis, and demonstrate the feasibility of incorporating compositional techniques in computer rendering. In addition to programming projects, this interdisciplinary research also consists of practices in visual arts. We present two art projects of digital photography and projection installation, which we built based on our theoretical analysis of composition and our software tools from the programming projects. Through these art projects, we evaluate our methodology by both making art ourselves and critiquing the resultant pieces with peer artists. From our point of view, it is important to be involved in art practices for rendering researchers, especially those who deal with aesthetic issues. The valuable first-hand experiences and the communications with artists in a visual arts context are rarely reported in the rendering literature. These experiences serve as effective guides for the future development of our research on computer rendering. The long term goal of our research is find a balance between artistic expression and realistic believability, based on the interdisciplinary knowledge of composition and perception, and implemented as either automated or user-assisted rendering tools. This goal may be termed as to achieve a staged realism, to synthesize images that are recognizable as depictions of realistic scenes, and at the same time enabling the freedom of composing the rendering results in an artistic manner. / Graduate / 0357 / 0984

Zugl.: Stuttgart, Univ., Habil.-Schr.

Zugl.: Saarbrücken, Univ., Diss., 2004