Computing object-based saliency in urban scenes using laser sensing
It becomes a well-known technology that a low-level map of complex environment containing 3D laser points can be generated using a robot with laser scanners. Given a cloud of 3D laser points of an urban scene, this paper proposes a method for locating the objects of interest, e.g. traffic signs or r...
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Published in | 2012 IEEE International Conference on Robotics and Automation pp. 4436 - 4443 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.05.2012
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Subjects | |
Online Access | Get full text |
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Summary: | It becomes a well-known technology that a low-level map of complex environment containing 3D laser points can be generated using a robot with laser scanners. Given a cloud of 3D laser points of an urban scene, this paper proposes a method for locating the objects of interest, e.g. traffic signs or road lamps, by computing object-based saliency. Our major contributions are: 1) a method for extracting simple geometric features from laser data is developed, where both range images and 3D laser points are analyzed; 2) an object is modeled as a graph used to describe the composition of geometric features; 3) a graph matching based method is developed to locate the objects of interest on laser data. Experimental results on real laser data depicting urban scenes are presented; efficiency as well as limitations of the method are discussed. |
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ISBN: | 9781467314039 146731403X |
ISSN: | 1050-4729 2577-087X |
DOI: | 10.1109/ICRA.2012.6224940 |