Out-of-core real-time visualization of massive 3D point clouds
Proceedings of the 7th International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa
Web-based 3D visualization for intelligent street lighting
Proceedings of the 16th International Conference on 3D Web Technology
Fast and robust generation of city-scale seamless 3D urban models
Computer-Aided Design
City-scale urban transport and dispersion simulation using geographic information system footprints
Proceedings of the 3rd International Conference on Computing for Geospatial Research and Applications
Reconstructing and exploring massive detailed cityscapes
VAST'11 Proceedings of the 12th International conference on Virtual Reality, Archaeology and Cultural Heritage
Semantic decomposition and reconstruction of residential scenes from LiDAR data
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
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The rapid and efficient creation of virtual environments has become a crucial part of virtual reality applications. In particular, civil and defense applications often require and employ detailed models of operations areas for training, simulations of different scenarios, planning for natural or man-made events, monitoring, surveillance, games, and films. A realistic representation of the large-scale environments is therefore imperative for the success of such applications since it increases the immersive experience of its users and helps reduce the difference between physical and virtual reality. However, the task of creating such large-scale virtual environments still remains a time-consuming and manual work. In this work, we propose a novel method for the rapid reconstruction of photorealistic large-scale virtual environments. First, a novel, extendible, parameterized geometric primitive is presented for the automatic building identification and reconstruction of building structures. In addition, buildings with complex roofs containing complex linear and nonlinear surfaces are reconstructed interactively using a linear polygonal and a nonlinear primitive, respectively. Second, we present a rendering pipeline for the composition of photorealistic textures, which unlike existing techniques, can recover missing or occluded texture information by integrating multiple information captured from different optical sensors (ground, aerial, and satellite).