Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00371-013-0827-z
Title: Textured mesh surface reconstruction of large buildings with multi-view stereo
Authors: Zhu, C.
Leow, W.K. 
Keywords: Building reconstruction
Mesh surface reconstruction
Multi-view stereo
Issue Date: Jun-2013
Citation: Zhu, C., Leow, W.K. (2013-06). Textured mesh surface reconstruction of large buildings with multi-view stereo. User Modeling and User-Adapted Interaction 29 (6-8) : 609-615. ScholarBank@NUS Repository. https://doi.org/10.1007/s00371-013-0827-z
Abstract: There are three main approaches for reconstructing 3D models of buildings. Laser scanning is accurate but expensive and limited by the laser's range. Structure-from-motion (SfM) and multi-view stereo (MVS) recover 3D point clouds from multiple views of a building. MVS methods, especially patch-based MVS, can achieve higher density than do SfM methods. Sophisticated algorithms need to be applied to the point clouds to construct mesh surfaces. The recovered point clouds can be sparse in areas that lack features for accurate reconstruction, making recovery of complete surfaces difficult. Moreover, segmentation of the building's surfaces from surrounding surfaces almost always requires some form of manual inputs, diminishing the ease of practical application of automatic 3D reconstruction algorithms. This paper presents an alternative approach for reconstructing textured mesh surfaces from point cloud recovered by patch-based MVS method. To a good first approximation, a building's surfaces can be modeled by planes or curve surfaces which are fitted to the point cloud. 3D points are resampled on the fitted surfaces in an orderly pattern, whose colors are obtained from the input images. This approach is simple, inexpensive, and effective for reconstructing textured mesh surfaces of large buildings. Test results show that the reconstructed 3D models are sufficiently accurate and realistic for 3D visualization in various applications. © 2013 Springer-Verlag Berlin Heidelberg.
Source Title: User Modeling and User-Adapted Interaction
URI: http://scholarbank.nus.edu.sg/handle/10635/78378
ISSN: 01782789
DOI: 10.1007/s00371-013-0827-z
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