Figure 1: We introduce a novel approach to GPU-based interactive procedural generation of the constitutive elements of largescale environments. This scene comprising 116K buildings and 561K trees is edited, generated and rendered at 7-12fps.
AbstractGPU Shape Grammars provide a solution for interactive procedural generation, tuning and visualization of massive environment elements for both video games and production rendering. Our technique generates detailed models without explicit geometry storage. To this end we reformulate the grammar expansion for generation of detailed models at the tesselation control and geometry shader stages. Using the geometry generation capabilities of modern graphics hardware, our technique generated massive, highly detailed models. GPU Shape Grammars integrate within a scalable framework by introducing automatic generation of levels of detail at reduced cost. We apply our solution for interactive generation and rendering of scenes containing thousands of buildings and trees.
ABSTRACT3D reconstruction of urban environments is a widely studied subject since several years, as it can lead to many useful applications: virtual navigation, augmented reality, architectural planification, etc. One of the most difficult problem nowadays in this context is the acquisition and treatment of very large scale data if precise reconstruction is aimed. In this paper we present a system for computing georeferenced positions and orientations of images of buildings from non calibrated videos. Providing such information is a mandatory step to well conditioned large scale and precise 3D reconstruction of urban areas. Our method is based on the registration of multimodal datasets, namely GPS measures, video sequences and rough 3D models of buildings.
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