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