Motion estimation with object based regularisation

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2525

Full metadata record

DC Field	Value	Language
dc.contributor.author	Panis, S	-
dc.contributor.author	Cosmas, J	-
dc.coverage.spatial	2	en
dc.date.accessioned	2008-07-24T12:00:37Z	-
dc.date.available	2008-07-24T12:00:37Z	-
dc.date.issued	1996	-
dc.identifier.citation	IEE Electronics Letters. 32 (10),872-873.	en
dc.identifier.issn	0013-5194	-
dc.identifier.uri	http://bura.brunel.ac.uk/handle/2438/2525	-
dc.description.abstract	A dynamic programming based matching method for motion estimation, that optimises a Bayesian maximum likelihood function in a 3-D optimisation space, is presented. The Bayesian function consists of a matching cost and an object based 2-D regularisation cost. The method gives results more accurate than block-based matching since the motion boundaries are close to the actual object boundaries.	en
dc.format.extent	465876 bytes	-
dc.format.mimetype	application/pdf	-
dc.language.iso	en	-
dc.publisher	IEE	en
dc.subject	Motion Estimation	en
dc.subject	Dynamic Programming	en
dc.title	Motion estimation with object based regularisation	en
dc.type	Research Paper	en
Appears in Collections:	Electronic and Computer Engineering Dept of Electronic and Electrical Engineering Research Papers

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