Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/4140
Title: A Framework for Automatic Modeling from Point Cloud Data
Authors: Poullis, Charalambos 
metadata.dc.contributor.other: Πουλλής, Χαράλαμπος
Major Field of Science: Engineering and Technology
Keywords: Segmentation;Clustering
Issue Date: 2-Apr-2014
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, vol. 35, no. 11, pp. 2563-2575
Volume: 35
Issue: 11
Start page: 2563
End page: 2575
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence 
Abstract: We propose a complete framework for the automatic modeling from point cloud data. Initially, the point cloud data are preprocessed into manageable datasets, which are then separated into clusters using a novel two-step, unsupervised clustering algorithm. The boundaries extracted for each cluster are then simplified and refined using a fast energy minimization process. Finally, three-dimensional models are generated based on the roof outlines. The proposed framework has been extensively tested, and the results are reported.
URI: https://hdl.handle.net/20.500.14279/4140
ISSN: 01628828
DOI: 10.1109/TPAMI.2013.64
Rights: © IEEE
Type: Article
Affiliation : Cyprus University of Technology 
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