An efficient approach to layered-depth image based rendering

Abstract

There exist a lot of computer graphics techniques to synthesize 3-D environments, of which, Image Based Rendering (IBR) techniques are becoming increasingly popular. In this thesis we concentrate on improving one such IBR technique, viz. Layered Depth Images (LDI). This technique, like many other IBR techniques, works on a set of pre-acquired imagery to model the world, and often, problems have been encountered in determining how exactly to decide on this pre-acquired set of sample images. As the quality of the synthetic view is governed by the initial stages of sampling, addressing this problem can enhance the result achieved by the eventual rendering engine.This research presents a new approach to rendering an LDI, by adaptively sampling the raw data based on the determined set of sample parameters. This approach eliminates the redundancy caused by over-sampling, and removes the hole artefact caused by under-sampling. In addition, the rendering speed of the LDI is improved by the pre-computed visibility graph and patch lookup table.