Progressive refinement rendering of implicit surfaces

The visualisation of implicit surfaces can be an inefficient task when such surfaces are complex and highly detailed. Visualising a surface by first converting it to a polygon mesh may lead to an excessive polygon count. Visualising a surface by direct ray casting is often a slow procedure. In this paper we present a progressive refinement renderer for implicit surfaces that are Lipschitz continuous. The renderer first displays a low resolution estimate of what the final image is going to be and, as the computation progresses, increases the quality of this estimate at an interactive frame rate. This renderer provides a quick previewing facility that significantly reduces the design cycle of a new and complex implicit surface. The renderer is also capable of completing an image faster than a conventional implicit surface rendering algorithm based on ray casting

Texture mapping with ray tracing

Includes bibliographical references leaves 56-59.Thesis (Master's)--Bilkent University, 1993.Ankara : The Department of Computer Engineering and Information Science and Institute of Engineering and Science of Bilkent University,1993.By using texture generation and global illumination techniques, it is possible to produce realistic computer images. Currently, ray tracing is one of the most popular global illumination techniques due to its simplicity, elegance, and easy implementation. In this thesis, texture mapping techniques are used with ray tracing to generate high quality visual effects. The implementation of the mapping process is presented and an approach for combining prefiltering techniques with ray tracing is introduced. General sweep surfaces produced by Topologybook are used for modeling.by Uğur Akdemir.M.S

Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields

Neural Radiance Field training can be accelerated through the use of grid-based representations in NeRF's learned mapping from spatial coordinates to colors and volumetric density. However, these grid-based approaches lack an explicit understanding of scale and therefore often introduce aliasing, usually in the form of jaggies or missing scene content. Anti-aliasing has previously been addressed by mip-NeRF 360, which reasons about sub-volumes along a cone rather than points along a ray, but this approach is not natively compatible with current grid-based techniques. We show how ideas from rendering and signal processing can be used to construct a technique that combines mip-NeRF 360 and grid-based models such as Instant NGP to yield error rates that are 8% - 76% lower than either prior technique, and that trains 22x faster than mip-NeRF 360.Comment: Project page: https://jonbarron.info/zipnerf

Image synthesis based on a model of human vision

Modern computer graphics systems are able to construct renderings of such high quality that viewers are deceived into regarding the images as coming from a photographic source. Large amounts of computing resources are expended in this rendering process, using complex mathematical models of lighting and shading. However, psychophysical experiments have revealed that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these visually important regions contain low-level visual feature differences that attract the attention of the viewer. This thesis will present a new approach to image synthesis that exploits these experimental findings by modulating the spatial quality of image regions by their visual importance. Efficiency gains are therefore reaped, without sacrificing much of the perceived quality of the image. Two tasks must be undertaken to achieve this goal. Firstly, the design of an appropriate region-based model of visual importance, and secondly, the modification of progressive rendering techniques to effect an importance-based rendering approach. A rule-based fuzzy logic model is presented that computes, using spatial feature differences, the relative visual importance of regions in an image. This model improves upon previous work by incorporating threshold effects induced by global feature difference distributions and by using texture concentration measures. A modified approach to progressive ray-tracing is also presented. This new approach uses the visual importance model to guide the progressive refinement of an image. In addition, this concept of visual importance has been incorporated into supersampling, texture mapping and computer animation techniques. Experimental results are presented, illustrating the efficiency gains reaped from using this method of progressive rendering. This visual importance-based rendering approach is expected to have applications in the entertainment industry, where image fidelity may be sacrificed for efficiency purposes, as long as the overall visual impression of the scene is maintained. Different aspects of the approach should find many other applications in image compression, image retrieval, progressive data transmission and active robotic vision

Volume ray casting techniques and applications using general purpose computations on graphics processing units

Traditional 3D computer graphics focus on rendering the exterior of objects. Volume rendering is a technique used to visualize information corresponding to the interior of an object, commonly used in medical imaging and other fields. Visualization of such data may be accomplished by ray casting; an embarrassingly parallel algorithm also commonly used in ray tracing. There has been growing interest in performing general purpose computations on graphics processing units (GPGPU), which are capable exploiting parallel applications and yielding far greater performance than sequential implementations on CPUs. Modern GPUs allow for rapid acceleration of volume rendering applications, offering affordable high performance visualization systems. This thesis explores volume ray casting performance and visual quality enhancements using the NVIDIA CUDA platform, and demonstrates how high quality volume renderings can be produced with interactive and real time frame rates on modern commodity graphics hardware. A number of techniques are employed in this effort, including early ray termination, super sampling and texture filtering. In a performance comparison of a sequential versus CUDA implementation on high-end hardware, the latter is capable of rendering 60 frames per second with an impressive price-performance ratio heavily favoring GPUs. A number of unique volume rendering applications are explored including multiple volume rendering capable of arbitrary placement and rigid volume registration, hypertexturing and stereoscopic anaglyphs, each greatly enhanced by the real time interaction of volume data. The techniques and applications discussed in this thesis may prove to be invaluable tools in fields such as medical and molecular imaging, flow and scientific visualization, engineering drawing and many others

Hardware accelerated computer graphics algorithms

The advent of shaders in the latest generations of graphics hardware, which has made consumer level graphics hardware partially programmable, makes now an ideal time to investigate new graphical techniques and algorithms as well as attempting to improve upon existing ones. This work looks at areas of current interest within the graphics community such as Texture Filtering, Bump Mapping and Depth of Field simulation. These are all areas which have enjoyed much interest over the history of computer graphics but which provide a great deal of scope for further investigation in the light of recent hardware advances. A new hardware implementation of a texture filtering technique, aimed at consumer level hardware, is presented. This novel technique utilises Fourier space image filtering to reduce aliasing. Investigation shows that the technique provides reduced levels of aliasing along with comparable levels of detail to currently popular techniques. This adds to the community's knowledge by expanding the range of techniques available, as well as increasing the number of techniques which offer the potential for easy integration with current consumer level graphics hardware along with real-time performance. Bump mapping is a long-standing and well understood technique. Variations and extensions of it have been popular in real-time 3D computer graphics for many years. A new hardware implementation of a technique termed Super Bump Mapping (SBM) is introduced. Expanding on the work of Cant and Langensiepen [1], the SBM technique adopts the novel approach of using normal maps which supply multiple vectors per texel. This allows the retention of much more detail and overcomes some of the aliasing deficiencies of standard bump mapping caused by the standard single vector approach and the non-linearity of the bump mapping process. A novel depth of field algorithm is proposed, which is an extension of the authors previous work [2][3][4]. The technique is aimed at consumer level hardware and attempts to raise the bar for realism by providing support for the 'see-through' effect. This effect is a vital factor in the realistic appearance of simulated depth of field and has been overlooked in real time computer graphics due to the complexities of an accurate calculation. The implementation of this new algorithm on current consumer level hardware is investigated and it is concluded that while current hardware is not yet capable enough, future iterations will provide the necessary functional and performance increases