A PHYSICAL SAMPLING METRIC FOR IMAGE-BASED COMPUTER GRAPHICS

Computer models of the real world often use images of the environment to capture realistic visual complexity. Image-based modeling techniques permit the creation of geometric models with a high level of visual detail from photographs. These models are textured by resampling these images of the scene; we call this process image-based texturing. The problem with traditional image-based texturing is the poor quality of the extracted textures, which are often blurred or stretched due to sampling problems. Furthermore, the extent of this degradation varies across the scene, due to dierences in the pose and position of the camera relative to each object in each image. This thesis makes two contributions to image-based computer graphics. First, it introduces a physically-based metric of sampling quality, based on the Jacobian matrix of the imaging transform, which captures the interaction of the imaging system with the imaged environment. This metric provides a direct, physical measure of the quality of resampled textures, and suggests a physical interpretatio