DocumentCode :
3062455
Title :
A comparison of terrain classification using local feature measurements of 3-dimensional colour point-cloud data
Author :
Gibbins, Danny ; Swierkowski, Leszek
Author_Institution :
Dept of Electr. & Electron. Eng., Univ. of Adelaide, Adelaide, SA, Australia
fYear :
2009
fDate :
23-25 Nov. 2009
Firstpage :
293
Lastpage :
298
Abstract :
This paper describes an examination of local feature measures for the classification of 3D range data collected using low cost sensors mounted on an unmanned air vehicle. Specifically this paper proposes and assesses the use of local metrics such as curvature, Zernike moments, colour and SPIN representations used in 3D object recognition for the labelling of terrain structures. The results of applying these features to sample data are presented. The classification scores achieved demonstrate that structures including vegetation, ditches and similar earthworks can be classified using such local feature estimates.
Keywords :
aerospace robotics; feature extraction; image classification; image colour analysis; object recognition; remotely operated vehicles; sensors; 3D colour point-cloud data; 3D object recognition; 3D range data collection; SPIN representations; Zernike moments; local feature measurements; terrain classification; terrain structures; unmanned air vehicle; Computer vision; Decision support systems; 3D reconstruction; feature estimation; range data; terrain analysis and classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference
Conference_Location :
Wellington
ISSN :
2151-2205
Print_ISBN :
978-1-4244-4697-1
Electronic_ISBN :
2151-2205
Type :
conf
DOI :
10.1109/IVCNZ.2009.5378392
Filename :
5378392
Link To Document :
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