Accurate depth based post-processing for perception enhancement in real time three-dimensional graphics
Authors: Jim X. Chen
Venue:  (2008)

Increased understanding of the importance of human visual perception within the computer graphics community is leading to new approaches in the way in which computer generated scenes are created. New techniques are being developed to simulate important aspects of the human visual system, such as depth cueing, in an effort to improve realism, and the sense of &lsquo;immersion&rsquo; of a participant. Yet many of these techniques require a trade-off between accuracy and performance, often resulting in specialized implementations that do not consider the need to integrate with other techniques or existing visualization systems. The main aim of the dissertation is to present and demonstrate new techniques for generating depth cueing effects for real-time rendering of high-quality interactive graphics. Depth cueing helps perceiving distance and space. When these cues are missing or inaccurately presented, the realism of the computer generated images is degraded. For example, most computer generated graphics lack depth of field; hence everything in the scene appears perfectly sharp. This dissertation applies new scene depth based techniques in generating real-time depth of field effect. We propose a new post-processing algorithm for accurate depth cueing effects in real time 3D graphics. Compared to existing work, our method will perform scene depth reconstruction on per pixel basis, decoupling it from the scene rendering process, and making it easy to integrate into existing visualization applications &ndash; a key aspect overlooked by existing implementations. Built on this scene depth reconstruction, we explore a new technique for restoring the full 3D fragment position; new algorithms for generating depth of field and layered fog are developed respectively for improved performance and quality. The new algorithms are designed to be executed entirely on the graphics processing unit (GPU), taking advantage of the parallelism of modern graphics cards and permitting real time perception enhancement effects. Our new depth of field algorithm performs two pass adaptive filtering in the post-processing step in the GPU, achieving real time frame rates and eliminating leakage artifacts. The new layered fog algorithm performs Euclidean distance fog integration along the line of sight using specialized fog density functions, similarly in the post-processing step with hardware acceleration, achieving high real time frame rates (3 ms for fog processing). In addition to ideally suited to a GPU implementation for achieving real time frame rates, both algorithms share the new accurate scene depth reconstruction algorithm resulting high quality images. In order to demonstrate the depth cueing effectively, a new comprehensive scene management application framework has been built. This application framework is capable of converting standard 3D scene world from VRML, 3ds, max, lightwave, etc to application recognizable format, then load, display, navigate and archive the scene world. The experimentations demonstrated that the post-processing effects are activated through a hook in the standard rendering pipe line, with minimum impact to the existing application and easy integration. The dissertation explores the realism of computer graphics from perception point of view and tackles the issues from a practical level. It provides ready to use algorithms for generating quality depth cueing effects in real time as well as integrated solutions to apply them to existing rendering systems.