The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6027

Full metadata record

DC Field	Value	Language
dc.creator	Grimson, W. Eric L.	-
dc.date	2004-10-04T14:36:16Z	-
dc.date	2004-10-04T14:36:16Z	-
dc.date	1989-05-01	-
dc.date.accessioned	2013-10-09T02:42:27Z	-
dc.date.available	2013-10-09T02:42:27Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1111	-
dc.identifier	http://hdl.handle.net/1721.1/6027	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	Many recognition systems use constrained search to locate objects in cluttered environments. Earlier analysis showed that the expected search is quadratic in the number of model and data features, if all the data comes from one object, but is exponential when spurious data is included. To overcome this, many methods terminate search once an interpretation that is "good enough" is found. We formally examine the combinatorics of this, showing that correct termination procedures dramatically reduce search. We provide conditions on the object model and the scene clutter such that the expected search is quartic. These results are shown to agree with empirical data for cluttered object recognition.	-
dc.format	30 p.	-
dc.format	3882593 bytes	-
dc.format	1505756 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1111	-
dc.subject	computer vision	-
dc.subject	object recognition	-
dc.subject	search	-
dc.subject	combinatorics	-
dc.title	The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments	-
Appears in Collections:	MIT Items

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