@conference {Zingaretti2007273,
	title = {Automatic extraction of LIDAR data classification rules},
	booktitle = {Proceedings - 14th International conference on Image Analysis and Processing, ICIAP 2007},
	year = {2007},
	note = {cited By 4},
	pages = {273-278},
	abstract = {LIDAR (Light Detection And Ranging) data are a primary data source for digital terrain model (DTM) generation and 3D city models. This paper presents an AdaBoost algorithm for the identification of rules for the classification of raw LIDAR data mainly as buildings, ground and vegetation. First raw data are filtered, interpolated over a grid and segmented. Then geometric and topological relationships among regions resulting from segmentation constitute the input to the tree-structured classification algorithm. Results obtained on data sets gathered over the town of Pavia (Italy) are compared with those obtained by a rule-based approach previously presented by the authors for the classification of the regions. {\textcopyright} 2007 IEEE.},
	doi = {10.1109/ICIAP.2007.4362791},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-48149101919\&partnerID=40\&md5=6578b3da6a7d08ffa58b7e9b97f98d95},
	author = {Primo Zingaretti and Emanuele Frontoni and G. Forlani and C. Nardinocchi}
}
@article {Forlani2006357,
	title = {Complete classification of raw LIDAR data and 3D reconstruction of buildings},
	journal = {Pattern Analysis and Applications},
	volume = {8},
	number = {4},
	year = {2006},
	note = {cited By 68},
	pages = {357-374},
	abstract = {LIDAR (LIght Detection And Ranging) data are a primary data source for digital terrain model (DTM) generation and 3D city models. This paper presents a three-stage framework for a robust automatic classification of raw LIDAR data as buildings, ground and vegetation, followed by a reconstruction of 3D models of the buildings. In the first stage the raw data are filtered and interpolated over a grid. In the second stage, first a double raw data segmentation is performed and then geometric and topological relationships among regions resulting from segmentation are computed and stored in a knowledge base. In the third stage, a rule-based scheme is applied for the classification of the regions. Finally, polyhedral building models are reconstructed by analysing the topology of building outlines, building roof slopes and eaves lines. Results obtained on data sets with different ground point density, gathered over the town of Pavia (Italy) with Toposys and Optech airborne laser scanning systems, are shown to illustrate the effectiveness of the proposed approach.},
	doi = {10.1007/s10044-005-0018-2},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-31944451659\&partnerID=40\&md5=55cd07722f1f7f4286ba71b656517b77},
	author = {G. Forlani and C. Nardinocchi and M. Scaioni and Primo Zingaretti}
}
