Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/2166
Title: | Photorealistic large-scale urban city model reconstruction | Authors: | Poullis, Charalambos You, Suya |
Major Field of Science: | Engineering and Technology | Field Category: | Civil Engineering | Keywords: | Large-scale modeling;Photorealistic model;Rrapid reconstruction | Issue Date: | Jul-2009 | Source: | Transactions on Visualization and Computer Graphics, 2009, vol. 15, no. 4, pp. 654-669 | Volume: | 15 | Issue: | 4 | Start page: | 654 | End page: | 669 | Journal: | Transactions on Visualization and Computer Graphics | Abstract: | 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). | URI: | https://hdl.handle.net/20.500.14279/2166 | ISSN: | 19410506 | DOI: | 10.1109/TVCG.2008.189 | Rights: | © IEEE. | Type: | Article | Affiliation: | University of Southern California | Affiliation : | University of Southern California | Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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