On the Verification of Hypothesized Matches in Model-Based Recognition

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

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