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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Bibliographic Details
Published in2012 IEEE International Conference on Robotics and Automation pp. 4436 - 4443
Main Authors Yipu Zhao, Mengwen He, Huijing Zhao, Davoine, F., Hongbin Zha
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
Feature extraction
Laser modes
Measurement by laser beam
Merging
Sensors
Vectors
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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.
ISBN:9781467314039
146731403X
ISSN:1050-4729
2577-087X
DOI:10.1109/ICRA.2012.6224940