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10

ICRA
2009
IEEE

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MMM-classification of 3D range data

13 years 2 months ago

MMM-classification of 3D range data

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This paper presents a method for accurately segmenting and classifying 3D range data into particular object classes. Object classification of input images is necessary for applications including robot navigation and automation, in particular with respect to path planning. To achieve robust object classification, we propose the idea of an object feature which represents a distribution of neighboring points around a target point. In addition, rather than processing raw points, we reconstruct polygons from the point data, introducing connectivity to the points. With these ideas, we can refine the Markov Random Field (MRF) calculation with more relevant information with regards to determining "related points". The algorithm was tested against five outdoor scenes and provided accurate classification even in the presence of many classes of interest.

Anuraag Agrawal, Atsushi Nakazawa, Haruo Takemura

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ICRA 2009 | Object Classification | Particular Object Classes | Robotics | Robust Object Classification |

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Added	19 Feb 2011
Updated	19 Feb 2011
Type	Journal
Year	2009
Where	ICRA
Authors	Anuraag Agrawal, Atsushi Nakazawa, Haruo Takemura

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