Model driven reconstruction of roofs from sparse LIDAR point clouds

Akaike, 1974, A new look at the statistical model identification, IEEE Transactions on Automatic Control, 19, 716, 10.1109/TAC.1974.1100705 Ameri, B., Fritsch, D., 2000. Automatic 3D building reconstruction using plane roof structures. In: Proc. of ASPRS Annual Conference, Washington, DC, 21–26 May. Baker, J.E., 1987. Reducing bias and inefficiency in the selection algorithm. In: Proc. 2nd International Conference on Genetic Algorithms (ICGA), Cambridge, MA, USA, July, pp. 14–21. Beder, C., Förstner, W., 2006. Direct solutions for computing cylinders from minimal sets of 3D points. In: Leonardis, A., Bischof, H., Pinz, A. (Eds.), Proc. of European Conference on Computer Vision (ECCV), Graz, Austria, 7–13 May, pp. 135–146. Bishop, 2007 Braun, A.C., Weidner, U., Hinz, S., 2011a. Classifying roof materials using data fusion through kernel composition – comparing ν-SVM and one-class SVM. In: Proc. of JURSE – Joint Urban Remote Sensing Event, Munich, Germany, 11–13 April, pp. 377–380. Braun, 2011, Integrating model knowledge into SVM classification – Fusing hyperspectral and laserscanning data by kernel composition, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 57 Brenner, 2000, Towards fully automatic generation of city models, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 33, 85 Brenner, 2005, Building reconstruction from images and laser scanning, International Journal of Applied Earth Observation and Geoinformation, 6, 187, 10.1016/j.jag.2004.10.006 Brenner, 1998, Rapid acquisition of virtual reality city models from multiple data sources, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 32, 323 Chang, 2011, LIBSVM: a library for support vector machines, ACM Transactions on Intelligent Systems and Technology, 2, 27:1, 10.1145/1961189.1961199 Chen, 2006, Combining SVMs with various feature selection strategies, 315 Cohen, 1960, A coefficent of agreement for nominal scales, Educational and Psychological Measurement, 20, 37, 10.1177/001316446002000104 Cord, M., Declercq, D., 1999. Bayesian model identification: application to building reconstruction in aerial imagery. In: Proc. of International Conference on Image Processing (ICIP ’99), Kobe, Japan, 24–28 October, pp. 140–144. Czerwinski, 2007, Sustainable SDI for EU noise mapping in NRW – best practice for INSPIRE, International Journal for Spatial Data Infrastructure Research, 2, 90 Döllner, J., Baumann, K., Buchholz, H., 2006. Virtual 3D city models as foundation of complex urban information spaces. In: Schrenk, M. (Ed.), Proc. 11. International conference on Urban Planning and Spatial Development in the Information Society (REAL CORP). CORP Competence Center of Urban and Regional Planning, Vienna, Austria, pp. 107–112. Dorninger, 2008, A comprehensive automated 3D approach for building extraction, reconstruction, and regularization from airborne laser scanning point clouds, Sensors, 8, 7323, 10.3390/s8117323 Duan, K.B., Keerthi, S.S., 2005. Which is the best multiclass SVM method? An empirical study. In: Proc of 6th International Workshop on Multiple Classifier Systems (MCS), Seaside, CA, USA, June 13–15, pp. 732–760. Fischler, 1981, Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, 24, 381, 10.1145/358669.358692 Gröger, G., Kolbe, T.H., Nagel, C., Häfele, K.H., 2012. OpenGIS City Geography Markup Language (CityGML) Encoding Standard. Version 2.0.0, Open Geospatial Consortium, OGC Doc. No. 12-019. Haala, 1998, 3D urban GIS from laser altimeter and 2D map data, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 32, 339 Haala, 2010, An update on automatic 3D building reconstruction, ISPRS Journal of Photogrammetry and Remote Sensing, 65, 570, 10.1016/j.isprsjprs.2010.09.006 Haitao, 2007, Fusion of high-resolution aerial imagery and LIDAR data for object-oriented urban land-cover classification based on SVM, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36, 179 Hartley, 2004 Henn, 2012, Automatic classification of building types in 3D city models – using SVMs for semantic enrichment of low resolution building data, GeoInformatica, 16, 281, 10.1007/s10707-011-0131-x Hsu, C.W., Chang, C.C., Lin., C.J., 2010. A practical guide to support vector classification. Technical Report. Department of Computer Science, National Taiwan University. Hu, 2003, Approaches to large-scale urban modeling, IEEE Computer Graphics and Applications, 23, 62, 10.1109/MCG.2003.1242383 Huang, 2010, Support Vector Machines for urban growth modelling, GeoInformatica, 14, 83, 10.1007/s10707-009-0077-4 Huang, H., Brenner, C., Sester, M., 2011. 3D building roof reconstruction from point clouds via generative models. In: Proc. of 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Chicago, Illinois, USA, 1–4 November, pp. 16–24. Huber, 1981 Hurvich, 1989, Regression and time series model selection in small samples, Biometrika, 76, 297, 10.1093/biomet/76.2.297 Kada, M., 2007. Scale-dependent simplification of 3D building models based on cell decomposition and primitive instancing. In: Proc. of the International Conference on Spatial Information Theory: COSIT 07, Melbourne, Australia, 19–23 September, pp. 222–237. Kada, 2009, 3D building reconstruction from LIDAR based on a cell decomposition approach, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 47 Knapp, S., Coors, V., 2008. The use of eparticipation in public participation: the VEPs example. In: Coors, V., Rumor, M., Fendel, E., Zlatanova, S. (Eds.), Proc. of the Urban Data Management Society Symposium 2007 (UDMS Annual 2007), Stuttgart, Germany, 10–12 October, pp. 93–104. Lafarge, 2010, Structural approach for building reconstruction from a single DSM, IEEE Transactions on Pattern Analysis and Machine Intelligence, 32, 135, 10.1109/TPAMI.2008.281 Lafarge, 2012, Creating large-scale city models from 3D-point clouds: a robust approach with hybrid representation, International Journal of Computer Vision, 99, 69, 10.1007/s11263-012-0517-8 Lodha, 2006, Aerial LiDAR data classification using support vector machines (SVM), 567 Maas, 1999, Two algorithms for extracting building models from raw laser altimetry data, ISPRS Journal of Photogrammetry and Remote Sensing, 54, 153, 10.1016/S0924-2716(99)00004-0 Niemeier, W., 2008. Ausgleichungsrechnung: Statistische Auswertemethoden. de Gruyter, Berlin, Germany (in German). Oude Elberink, 2009, Target graph matching for building reconstruction, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 49 Overby, 2004, Automatic 3D building reconstruction from airborne laser scanning and cadastral data using hough transform, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 35, 296 Platt, 1999, Fast training of support vector machines using sequential minimal optimization, 185 Platt, 1999, Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods, 61 Poullis, 2009, Photorealistic large-scale urban city model reconstruction, IEEE Transactions on Visualization and Computer Graphics, 15, 654, 10.1109/TVCG.2008.189 Quinlan, 1993 Römer, 2010, Identifying Architectural Style in 3D City Models with Support Vector Machines, Photogrammetrie, Fernerkundung, Geoinformation (PFG), 5, 369 Rottensteiner, 2006, Consistent estimation of building parameters considering geometric regularities by soft constraints, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36, 93 Rottensteiner, 2003, Automatic generation of building models from LIDAR data and the integration of aerial images, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 34, 174 Rottensteiner, 2005, Automated Delineation of Roof Planes from LIDAR Data, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36, 221 Rumpf, 2012, Sequential support vector machine classification for small-grain weed species discrimination with special regard to cirsium arvense and galium aparine, Computers and Electronics in Agriculture, 80, 89, 10.1016/j.compag.2011.10.018 Schmittwilken, J., 2012. Attributierte Grammatiken zur Rekonstruktion und Interpretation von Fassaden. Ph.D. thesis. Institute for Geodesy and Geoinformation, University of Bonn, Bonn, Germany. <http://hss.ulb.uni-bonn.de/2012/2780/2780.htm> (in German). Schmittwilken, 2010, Model-based reconstruction and classification of facade parts in 3D point clouds, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 269 Schmittwilken, 2007, A Semantic Model of Stairs in Building Collars, Photogrammetrie, Fernerkundung, Geoinformation (PFG), 6, 415 Schnabel, R., Wessel, R., Wahl, R., Klein, R., 2008. Shape recognition in 3D point-clouds. In: Skala, V. (Ed.), Proc. of the 16-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, Plzen-Bory, Czech Republic, 4–7 February, pp. 65–72. Schölkopf, 2002 Scholze, 2001, A probabilistic approach to roof patch extraction and reconstruction, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 34, 195 Suveg, 2004, Reconstruction of 3D building models from aerial images and maps, ISPRS Journal of Photogrammetry and Remote Sensing, 58, 202, 10.1016/j.isprsjprs.2003.09.006 Tarsha-Kurdi, 2008, Extended RANSAC algorithm for automatic detection of building roof planes from LIDAR data, The Photogrammetric Journal of Finland, 21, 97 Tarsha-Kurdi, 2007, Model-driven and data-driven approaches using LIDAR data : analysis and comparison, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36, 87 Thrun, 2005 Torr, 2000, MLESAC: a new robust estimator with application to estimating image geometry, Journal of Computer Vision and Image Understanding, 78, 138, 10.1006/cviu.1999.0832 Vallet, 2011, Building footprint database improvement for 3D reconstruction: a split and merge approach and its evaluation, ISPRS Journal of Photogrammetry and Remote Sensing, 66, 732, 10.1016/j.isprsjprs.2011.06.005 Vapnik, 1998 Verma, V., Kumar, R., Hsu, S.C., 2006. 3D building detection and modeling from aerial LIDAR data. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), New York, NY, USA, 17–22 June, pp. 2213–2220. Vosselman, 2012, Automated planimetric quality control in high accuracy airborne laser scanning surveys, ISPRS Journal of Photogrammetry and Remote Sensing, 74, 90, 10.1016/j.isprsjprs.2012.09.002 Vosselman, 2001, 3D building model reconstruction from point clouds and ground plans, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 34, 37 Vosselman, 2010 Zhou, Q.Y., Neumann, U., 2009. A streaming framework for seamless building reconstruction from large-scale aerial LiDAR data. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, FL, USA, 20–25 June, pp. 2759–2766. Zhou, Q.Y., Neumann, U., 2012. 2.5D building modeling by discovering global regularities. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA, 26–21 June, pp. 326–333.