View-dependent image-based techniques for fast rendering of complex environments

One of the primary goals of computer graphics has been the creation of interactive photorealistic imagery. Unfortunately, the dual objectives of interactivity and photorealism are at odds with each other. Image-based rendering provides a method whereby an offline, computationally intensive image synthesis or computer vision algorithm can be paired with an online, interactive image synthesis algorithm to produce real-time renderings of complex scenes. This dissertation presents three novel view-dependent image-based representations that can be used to accelerate rendering of complex, naturalistic scenes. Hierarchical Image Caching automatically and dynamically caches parts of a scene into images that are rendered in place of geometry, at a much lower computational cost. Layered Depth Images efficiently render complex scenes in software using an image-order warp of pixels with associated depth. Storing multiple depth pixels along each ray of an image, a scene is sampled into a sparse, compact data structure in a view-dependent fashion. Tiling Layered Depth Images uses Layered Depth Images as a basic modeling primitive to create expansive renderings of richly textured terrains. A novel stochastic tiling algorithm is given that guarantees non-periodic tilings of the plane while using a small set of square tiles and a simple construction procedure. Lastly, all image-based representations can be cast as approximations to the plenoptic function, a seven dimensional function describing all of the light in a scene. A novel classification is presented that relates image-based representations, such as the three outlined above, through four common techniques used to reduce the complexity of the plenoptic function.