Affiliation:
1. University of North Carolina at Chapel Hill
Abstract
We present an incremental algorithm to compute image-based simplifications of a large environment. We use an optimization-based approach to generate samples based on scene visibility, and from each viewpoint create textured depth meshes (TDMs) using sampled range panoramas of the environment. The optimization function minimizes artifacts such as skins and cracks in the reconstruction. We also present an encoding scheme for multiple TDMs that exploits spatial coherence among different viewpoints. The resulting simplifications, incremental textured depth meshes (ITDMs), reduce preprocessing, storage, rendering costs and visible artifacts. Our algorithm has been applied to large, complex synthetic environments comprising millions of primitives. It is able to render them at 20 -- 40 frames a second on a PC with little loss in visual fidelity.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design
Cited by
13 articles.
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