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Robust and Efficient 3D Recognition by Alignment

dc.date.accessioned2004-10-20T19:55:26Z
dc.date.accessioned2018-11-24T10:21:54Z
dc.date.available2004-10-20T19:55:26Z
dc.date.available2018-11-24T10:21:54Z
dc.date.issued1992-09-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6799
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/6799
dc.description.abstractAlignment is a prevalent approach for recognizing 3D objects in 2D images. A major problem with current implementations is how to robustly handle errors that propagate from uncertainties in the locations of image features. This thesis gives a technique for bounding these errors. The technique makes use of a new solution to the problem of recovering 3D pose from three matching point pairs under weak-perspective projection. Furthermore, the error bounds are used to demonstrate that using line segments for features instead of points significantly reduces the false positive rate, to the extent that alignment can remain reliable even in cluttered scenes.en_US
dc.format.extent113 p.en_US
dc.format.extent903052 bytes
dc.format.extent1830006 bytes
dc.language.isoen_US
dc.subjectcomputer visionen_US
dc.subjectobject recognitionen_US
dc.subjecterror modelsen_US
dc.subjectsalignmenten_US
dc.subjectweak perspectiveen_US
dc.subjectpose estimationen_US
dc.titleRobust and Efficient 3D Recognition by Alignmenten_US


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