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ICPR
2008
IEEE

Model-based visual self-localization using geometry and graphs

13 years 9 months ago
Model-based visual self-localization using geometry and graphs
In this paper, a geometric approach for global selflocalization based on a world-model and active stereo vision is introduced. The method uses class specific object recognition algorithms to obtain the location of entities within the surroundings. The perceived entities in recognition trials are simultaneously filtered and fused to provide a robust set of class features. These classified perceptions which simultaneously satisfy geometric and topological constraints are employed for pruning purposes upon the world-model generating the location hypotheses set. Finally, the hypotheses are validated and disambiguated by applying visual recognition algorithms to selected entities of the world-model. The proposed approach has been successfully used with a humanoid robot.
David Israel Gonzalez-Aguirre, Tamim Asfour, Eduar
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICPR
Authors David Israel Gonzalez-Aguirre, Tamim Asfour, Eduardo Bayro-Corrochano, Rüdiger Dillmann
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