Potential negative obstacle detection by occlusion labeling

In this paper, we present an approach for potential negative obstacle detection, based on missing data interpretation that extends traditional techniques driven by data only, which capture the occupancy of the scene. The approach is decomposed into three steps: three-dimensional (3D) data accumulati...

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Bibliographic Details
Published in2007 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 2168 - 2173
Main Authors Heckman, N., Lalonde, J.-F., Vandapel, N., Hebert, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2007
Subjects
Cameras
Intelligent robots
Labeling
Laser radar
Layout
Mobile robots
Optical propagation
Remotely operated vehicles
Robot sensing systems
Robot vision systems
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ISBN9781424409112
142440911X
ISSN2153-0858
DOI10.1109/IROS.2007.4398970

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Summary:In this paper, we present an approach for potential negative obstacle detection, based on missing data interpretation that extends traditional techniques driven by data only, which capture the occupancy of the scene. The approach is decomposed into three steps: three-dimensional (3D) data accumulation and low level classification, 3D occluder propagation, and context-based occlusion labeling. The approach is validated using logged laser data collected in various outdoor natural terrains and also demonstrated live on-board the Demo-III experimental unmanned vehicle (XUV).
ISBN:9781424409112
142440911X
ISSN:2153-0858
DOI:10.1109/IROS.2007.4398970