CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2013 vol.35 Issue No.11 - Nov.
Issue No.11 - Nov. (2013 vol.35)
C. Poullis , Immersive & Creative Technol. Lab., Cyprus Univ. of Technol., Limassol, Cyprus
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2013.64
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.
Data models, Three-dimensional displays, Vectors, Solid modeling, Surface treatment, Clustering algorithms, Covariance matrices,shape refinement, Three-dimensional reconstruction, 3D modeling, point cloud, clustering, segmentation
C. Poullis, "A Framework for Automatic Modeling from Point Cloud Data", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.35, no. 11, pp. 2563-2575, Nov. 2013, doi:10.1109/TPAMI.2013.64