Computer graphics imagery (CGI) has enabled many useful applications in training, defense, and entertainment. One such application, CGI simulation, is a real-time system that allows users to navigate through and interact with a virtual rendition of an existing environment. Creating such systems is difficult, but particularly burdensome is the task of designing and constructing the internal representation of the simulation content. Authoring this content on a computer usually requires great expertise and many man-hours of labor. Computational stereo and image-based rendering offer possibilities to automatically create simulation content without user assistance. However, these technologies have largely been limited to creating content from only a few photographs, severely limiting the simulation experience. The purpose of this dissertation is to enable the process of automated content creation for large numbers of photographs. The workflow goal consists of a user photographing any real-world environment intended for simulation, and then loading the photographs into the computer. The theoretical and algorithmic contributions of the dissertation are then used to transform the photographs into the data required for real-time exploration of the photographed locale. This permits a rich simulation experience without the laborious effort required to author the content manually. To approach this goal we make four contributions to the fields of computer vision and image-based rendering: an improved point correspondence methodology, an adjacency graph construction algorithm for unordered photographs, a pose estimation ordering for unordered image sets, and an image-based rendering algorithm that interpolates omnidirectional images to synthesize novel views. We encapsulate our contributions into a working system that we call Vision-Based Rendering (VBR). With our VBR system we are able to automatically create simulation content from a large unordered collection of input photographs. However, there are severe restrictions in the type of image content our present system can accurately simulate. Photographs containing large regions of high frequency detail are incorporated very accurately, but images with smooth color gradations, including most indoor photographs, create distracting artifacts in the final simulation. Thus our system is a significant and functional step toward the ultimate goal of simulating any real-world environment.
College and Department
Physical and Mathematical Sciences; Computer Science
BYU ScholarsArchive Citation
Steele, Kevin L., "Vision-Based Rendering: Using Computational Stereo to Actualize IBR View Synthesis" (2006). All Theses and Dissertations. 1158.
Computer Vision, Image-based Rendering, Computational Stereo, Camera Pose Estimation