| Recent developments in image-based modeling and rendering provide significant advantages over traditional image synthesis process, including improved realism, simple representation and automatic content creation. Representations such as Plenoptic Modeling, Light Field, and the Lumigraph are well suited for storing view-dependent radiance information for static scenes and objects. Unfortunately, these representations have much higher storage requirement than traditional approaches, and the acquisition process demands very dense sampling of radiance data. With the assist of geometric information, the sampling density of image-based representations can be greatly reduced, and the radiance data can potentially be represented more compactly. One such parameterization, called Surface Light Field, offers natural and intuitive description of the complex radiance data. However, issues including encoding and rendering efficiency present significant challenges to its practical application.; In this dissertation, I present a method for efficient representation and interactive visualization of surface light fields. I propose to partition the radiance data over elementary surface primitives and to approximate each partitioned data by a small set of lower-dimensional discrete functions. By utilizing graphics hardware features, the proposed rendering algorithm decodes directly from this compact representation at interactive frame rates on a personal computer. Since the approximations are represented as texture maps, I refer to the proposed method as Light Field Mapping. The approximations can be further compressed using standard image compression techniques leading to extremely compact data sets that are up to four orders of magnitude smaller than the uncompressed light field data. I demonstrate the proposed representation through a variety of non-trivial physical and synthetic scenes and objects scanned through acquisition systems designed for capturing both small and large-scale scenes. |
PDF Full Text Request