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12

ICRA
1999
IEEE

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3-D Cueing: A Data Filter for Object Recognition

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3-D Cueing: A Data Filter for Object Recognition

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This paper presents a novel method for quickly filtering range data points to make object recognition in large 3D data sets feasible. The general approach, called "3D cueing," uses shape signatures from object models as the basis for a fast, probabilistic classification system which rates scene points in terms of their likelihood of belonging to a model. This algorithm, which could be used as a front-end for any traditional 3D matching technique, is demonstrated using several models and cluttered scenes in which the model occupies between 1% and 50% of the data points.

Owen T. Carmichael, Martial Hebert

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Data Points | ICRA 1999 | Large 3D Data | Range Data Points | Robotics |

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Added	03 Aug 2010
Updated	03 Aug 2010
Type	Conference
Year	1999
Where	ICRA
Authors	Owen T. Carmichael, Martial Hebert

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