On the Verification of Hypothesized Matches in Model-Based Recognition

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6028

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DC Field	Value	Language
dc.creator	Grimson, W. Eric L.	-
dc.creator	Huttenlocher, Daniel P.	-
dc.date	2004-10-04T14:36:17Z	-
dc.date	2004-10-04T14:36:17Z	-
dc.date	1989-05-01	-
dc.date.accessioned	2013-10-09T02:42:27Z	-
dc.date.available	2013-10-09T02:42:27Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1110	-
dc.identifier	http://hdl.handle.net/1721.1/6028	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	In model-based recognition, ad hoc techniques are used to decide if a match of data to model is correct. Generally an empirically determined threshold is placed on the fraction of model features that must be matched. We rigorously derive conditions under which to accept a match, relating the probability of a random match to the fraction of model features accounted for, as a function of the number of model features, number of image features and the sensor noise. We analyze some existing recognition systems and show that our method yields results comparable with experimental data.	-
dc.format	23 p.	-
dc.format	3009307 bytes	-
dc.format	1200576 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1110	-
dc.subject	object recognition	-
dc.subject	search	-
dc.subject	model-based vision	-
dc.title	On the Verification of Hypothesized Matches in Model-Based Recognition	-
Appears in Collections:	MIT Items

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