Model-Based Matching of Line Drawings by Linear Combinations of Prototypes

dc.creator	Jones, Michael J.
dc.creator	Poggio, Tomaso
dc.date	2004-10-20T20:49:13Z
dc.date	2004-10-20T20:49:13Z
dc.date	1996-01-18
dc.date.accessioned	2013-10-09T02:48:29Z
dc.date.available	2013-10-09T02:48:29Z
dc.date.issued	2013-10-09
dc.identifier	AIM-1559
dc.identifier	CBCL-128
dc.identifier	http://hdl.handle.net/1721.1/7187
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	We describe a technique for finding pixelwise correspondences between two images by using models of objects of the same class to guide the search. The object models are 'learned' from example images (also called prototypes) of an object class. The models consist of a linear combination ofsprototypes. The flow fields giving pixelwise correspondences between a base prototype and each of the other prototypes must be given. A novel image of an object of the same class is matched to a model by minimizing an error between the novel image and the current guess for the closest modelsimage. Currently, the algorithm applies to line drawings of objects. An extension to real grey level images is discussed.
dc.format	7 p.
dc.format	442803 bytes
dc.format	265964 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-1559
dc.relation	CBCL-128
dc.subject	AI
dc.subject	MIT
dc.subject	Artificial Intelligence
dc.subject	computer vision
dc.subject	scorrespondence
dc.subject	model-based matching
dc.title	Model-Based Matching of Line Drawings by Linear Combinations of Prototypes

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