Mid-Level Vision and Recognition of Non-Rigid Objects

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6792

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DC Field	Value	Language
dc.creator	Subirana-Vilanova, J. Brian	-
dc.date	2004-10-20T19:55:13Z	-
dc.date	2004-10-20T19:55:13Z	-
dc.date	1995-04-01	-
dc.date.accessioned	2013-10-09T02:46:56Z	-
dc.date.available	2013-10-09T02:46:56Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AITR-1442	-
dc.identifier	http://hdl.handle.net/1721.1/6792	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	We address mid-level vision for the recognition of non-rigid objects. We align model and image using frame curves - which are object or "figure/ground" skeletons. Frame curves are computed, without discontinuities, using Curved Inertia Frames, a provably global scheme implemented on the Connection Machine, based on: non-cartisean networks; a definition of curved axis of inertia; and a ridge detector. I present evidence against frame alignment in human perception. This suggests: frame curves have a role in figure/ground segregation and in fuzzy boundaries; their outside/near/top/ incoming regions are more salient; and that perception begins by setting a reference frame (prior to early vision), and proceeds by processing convex structures.	-
dc.format	239 p.	-
dc.format	48192029 bytes	-
dc.format	2356367 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AITR-1442	-
dc.subject	vision	-
dc.title	Mid-Level Vision and Recognition of Non-Rigid Objects	-
Appears in Collections:	MIT Items

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