On the Sensitivity of the Hough Transform for Object Recognition

dc.creator	Grimson, W. Eric L.
dc.creator	Huttenlocher, David
dc.date	2004-10-04T14:36:40Z
dc.date	2004-10-04T14:36:40Z
dc.date	1988-05-01
dc.date.accessioned	2013-10-09T02:42:30Z
dc.date.available	2013-10-09T02:42:30Z
dc.date.issued	2013-10-09
dc.identifier	AIM-1044
dc.identifier	http://hdl.handle.net/1721.1/6039
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	A common method for finding an object's pose is the generalized Hough transform, which accumulates evidence for possible coordinate transformations in a parameter space and takes large clusters of similar transformations as evidence of a correct solution. We analyze this approach by deriving theoretical bounds on the set of transformations consistent with each data-model feature pairing, and by deriving bounds on the likelihood of false peaks in the parameter space, as a function of noise, occlusion, and tessellation effects. We argue that blithely applying such methods to complex recognition tasks is a risky proposition, as the probability of false positives can be very high.
dc.format	40 p.
dc.format	5359682 bytes
dc.format	2031093 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-1044
dc.subject	Hough transform
dc.subject	object recognition
dc.title	On the Sensitivity of the Hough Transform for Object Recognition

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