Recognizing Indoor Scenes

dc.creator	Torralba, Antonio
dc.creator	Sinha, Pawan
dc.date	2004-10-20T21:03:41Z
dc.date	2004-10-20T21:03:41Z
dc.date	2001-07-25
dc.date.accessioned	2013-10-09T02:48:37Z
dc.date.available	2013-10-09T02:48:37Z
dc.date.issued	2013-10-09
dc.identifier	AIM-2001-015
dc.identifier	CBCL-202
dc.identifier	http://hdl.handle.net/1721.1/7236
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	We propose a scheme for indoor place identification based on the recognition of global scene views. Scene views are encoded using a holistic representation that provides low-resolution spatial and spectral information. The holistic nature of the representation dispenses with the need to rely on specific objects or local landmarks and also renders it robust against variations in object configurations. We demonstrate the scheme on the problem of recognizing scenes in video sequences captured while walking through an office environment. We develop a method for distinguishing between 'diagnostic' and 'generic' views and also evaluate changes in system performances as a function of the amount of training data available and the complexity of the representation.
dc.format	17 p.
dc.format	14931961 bytes
dc.format	3219314 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-2001-015
dc.relation	CBCL-202
dc.subject	AI
dc.subject	Scene classification
dc.subject	Navigation
dc.subject	scene representation
dc.title	Recognizing Indoor Scenes

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