Recognizing 3-D Objects Using 2-D Images

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6796

Full metadata record

DC Field	Value	Language
dc.creator	Jacobs, David W.	-
dc.date	2004-10-20T19:55:20Z	-
dc.date	2004-10-20T19:55:20Z	-
dc.date	1993-04-01	-
dc.date.accessioned	2013-10-09T02:46:58Z	-
dc.date.available	2013-10-09T02:46:58Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AITR-1416	-
dc.identifier	http://hdl.handle.net/1721.1/6796	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	We discuss a strategy for visual recognition by forming groups of salient image features, and then using these groups to index into a data base to find all of the matching groups of model features. We discuss the most space efficient possible method of representing 3-D models for indexing from 2-D data, and show how to account for sensing error when indexing. We also present a convex grouping method that is robust and efficient, both theoretically and in practice. Finally, we combine these modules into a complete recognition system, and test its performance on many real images.	-
dc.format	269 p.	-
dc.format	3519825 bytes	-
dc.format	7005877 bytes	-
dc.format	application/octet-stream	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AITR-1416	-
dc.subject	grouping	-
dc.subject	indexing	-
dc.subject	recognition	-
dc.subject	invariants	-
dc.subject	sensing erro	-
dc.subject	snon-accidental properties	-
dc.title	Recognizing 3-D Objects Using 2-D Images	-
Appears in Collections:	MIT Items

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