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URN: urn:nbn:de:swb:90-674659
Originalveröffentlichung
DOI: 10.5194/isprs-annals-III-3-169-2016

Classification of airborne laser scanning data using geometric multi-scale features and different neighbourhood types

Blomley, R.; Jutzi, B.; Weinmann, M.

Abstract:
In this paper, we address the classification of airborne laser scanning data. We present a novel methodology relying on the use of complementary types of geometric features extracted from multiple local neighbourhoods of different scale and type. To demonstrate the performance of our methodology, we present results of a detailed evaluation on a standard benchmark dataset and we show that the consideration of multi-scale, multi-type neighbourhoods as the basis for feature extraction leads to improved classification results in comparison to single-scale neighbourhoods as well as in comparison to multi-scale neighbourhoods of the same type.


Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Jahr 2016
Sprache Englisch
Identifikator ISSN: 2194-9050

KITopen-ID: 1000067465
HGF-Programm 12.04 (POF III, LK 01)
Erschienen in ISPRS annals
Heft 3
Seiten 169-176
Bemerkung zur Veröffentlichung XXIII ISPRS Congress, Praha, CZ, July 12-19, 2016. Commission III
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