A Self-Organizing Multiple-View Representation of 3D Objects

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6514

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DC Field	Value	Language
dc.creator	Edelman, Shimon	-
dc.creator	Weinshall, Daphna	-
dc.date	2004-10-04T15:14:24Z	-
dc.date	2004-10-04T15:14:24Z	-
dc.date	1989-08-01	-
dc.date.accessioned	2013-10-09T02:45:52Z	-
dc.date.available	2013-10-09T02:45:52Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1146	-
dc.identifier	http://hdl.handle.net/1721.1/6514	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	We explore representation of 3D objects in which several distinct 2D views are stored for each object. We demonstrate the ability of a two-layer network of thresholded summation units to support such representations. Using unsupervised Hebbian relaxation, we trained the network to recognise ten objects from different viewpoints. The training process led to the emergence of compact representations of the specific input views. When tested on novel views of the same objects, the network exhibited a substantial generalisation capability. In simulated psychophysical experiments, the network's behavior was qualitatively similar to that of human subjects.	-
dc.format	2399506 bytes	-
dc.format	1875063 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1146	-
dc.title	A Self-Organizing Multiple-View Representation of 3D Objects	-
Appears in Collections:	MIT Items

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