Automatic extraction of LIDAR data classification rules

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	Similar Articles Articles by Primo Zingaretti Articles by Emanuele Frontoni Articles by Gianfranco Forlani Articles by Carla Nardinocchi

14th International Conference on Image Analysis and Processing (ICIAP 2007)

Modena, Italy

September 10-September 14

ISBN: 0-7695-2877-5

	ASCII Text	x
	Primo Zingaretti, Emanuele Frontoni, Gianfranco Forlani, Carla Nardinocchi, "Automatic extraction of LIDAR data classification rules," Image Analysis and Processing, International Conference on, pp. 273-278, 14th International Conference on Image Analysis and Processing (ICIAP 2007), 2007.

	BibTex	x
	@article{ 10.1109/ICIAP.2007.31, author = {Primo Zingaretti and Emanuele Frontoni and Gianfranco Forlani and Carla Nardinocchi}, title = {Automatic extraction of LIDAR data classification rules}, journal ={Image Analysis and Processing, International Conference on}, volume = {0}, year = {2007}, isbn = {0-7695-2877-5}, pages = {273-278}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICIAP.2007.31}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Image Analysis and Processing, International Conference on TI - Automatic extraction of LIDAR data classification rules SN - 0-7695-2877-5 SP273 EP278 A1 - Primo Zingaretti, A1 - Emanuele Frontoni, A1 - Gianfranco Forlani, A1 - Carla Nardinocchi, PY - 2007 KW - null VL - 0 JA - Image Analysis and Processing, International Conference on ER -

Primo Zingaretti, Universita Politecnica delle Marche, Italy

Emanuele Frontoni, Universita Politecnica delle Marche, Italy

Gianfranco Forlani, Universita di Parma, Italy

Carla Nardinocchi, Universita di Roma "La Sapienza", Italy

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICIAP.2007.31

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.

Citation:

Primo Zingaretti, Emanuele Frontoni, Gianfranco Forlani, Carla Nardinocchi, "Automatic extraction of LIDAR data classification rules," iciap, pp.273-278, 14th International Conference on Image Analysis and Processing (ICIAP 2007), 2007

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