DocumentCode :
440203
Title :
Robust object segmentation and parametrization of 3D lidar data
Author :
Kapp, Andreas
Author_Institution :
Inst. fur Mess- und Regelungstechnik, Karlsruhe Univ., Germany
fYear :
2005
fDate :
6-8 June 2005
Firstpage :
694
Lastpage :
699
Abstract :
This article addresses the problem of robust signal processing of 3D lidar data prone to noise. After describing the characteristics of the lidar data given we describe how the data can be segmented in a robust manner. The approach is based on edge detection followed by region growing. We show how the segments can be described using parametric models. In the final step the segments are circumscribed using appropriate bounding objects. We motivate the individual steps of our approach and light up the mathematical background.
Keywords :
automated highways; edge detection; image segmentation; object detection; optical radar; 3D lidar data; edge detection; object parametrization; object segmentation; region growing; robust signal processing; Goniometers; Image edge detection; Image segmentation; Integrated circuit noise; Laser radar; Noise robustness; Object segmentation; Parameter estimation; Signal processing; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2005. Proceedings. IEEE
Print_ISBN :
0-7803-8961-1
Type :
conf
DOI :
10.1109/IVS.2005.1505184
Filename :
1505184
Link To Document :
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