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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/76779
- Range segmentation of large building exteriors: a hierarchical robust approach
- Hesami, Reyhaneh; Bab-Hadiashar, Alireza; HosseinNezhad, Reza
- There are three main challenging issues associated with processing range data of large-scale outdoor scene: (a) significant disparity in the size of features, (b) existence of complex and multiple structures; and (c) high uncertainty in data due to the construction error or moving objects. Existing range segmentation methods in computer vision literature have been generally developed for laboratory-sized objects or shapes with simple geometric features and do not address these issues. This paper studies the main problems involved in segmenting the range data of large building exteriors and presents a robust hierarchical segmentation strategy to extract fine as well as large details from such data. The proposed method employs a high breakdown robust estimator in a coarse-to-fine approach to deal with the existing discrepancies in size and sampling rates of various features of large outdoor objects. The segmentation algorithm is tested on several outdoor range datasets obtained by different laser rangescanners. The results show that the proposed method is an accurate and computationally cost-effective tool that facilitates automatic generation of 3D models of large-scale objects in general and building exteriors in particular.
- Publication type
- Journal article
- Research centre
- Swinburne University of Technology. Faculty of Engineering and Industrial Sciences
- Computer Vision and Image Understanding, Vol. 114, no. 4 (Apr 2010), pp. 475-490
- Publication year
- Historical building exteriors; Large-scale range data; Range segmentation; Robust estimation
- Academic Press
- Publisher URL
- Copyright © 2009 Elsevier Inc. All rights reserved.
- Peer reviewed