Title :
Computing object-based saliency in urban scenes using laser sensing
Author :
Zhao, Yipu ; He, Mengwen ; Zhao, Huijing ; Davoine, Franck ; Zha, Hongbin
Author_Institution :
State Key Lab. of Machine Perception (MOE), Peking Univ., Beijing, China
Abstract :
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.
Keywords :
computational geometry; feature extraction; graph theory; mobile robots; object detection; optical scanners; robot vision; 3D laser points; geometric feature extraction; graph matching based method; laser scanners; laser sensing; object detection; object location; object-based saliency computation; road lamps; traffic signs; urban scenes; Feature extraction; Laser modes; Measurement by laser beam; Merging; Sensors; Vectors;
Conference_Titel :
Robotics and Automation (ICRA), 2012 IEEE International Conference on
Conference_Location :
Saint Paul, MN
Print_ISBN :
978-1-4673-1403-9
Electronic_ISBN :
1050-4729
DOI :
10.1109/ICRA.2012.6224940