Literature DB >> 19423889

Photorealistic large-scale urban city model reconstruction.

Charalambos Poullis1, Suya You.   

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).

Entities:  

Year:  2009        PMID: 19423889     DOI: 10.1109/TVCG.2008.189

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  1 in total

1.  Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

Authors:  Rongyong Huang; Shunyi Zheng; Kun Hu
Journal:  Sensors (Basel)       Date:  2018-06-01       Impact factor: 3.576

  1 in total

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