Why Stereo Vision is Not Always About 3D Reconstruction

dc.creator	Grimson, W. Eric L.
dc.date	2004-10-04T14:15:53Z
dc.date	2004-10-04T14:15:53Z
dc.date	1993-07-01
dc.date.accessioned	2013-10-09T02:42:04Z
dc.date.available	2013-10-09T02:42:04Z
dc.date.issued	2013-10-09
dc.identifier	AIM-1435
dc.identifier	http://hdl.handle.net/1721.1/5947
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	It is commonly assumed that the goal of stereovision is computing explicit 3D scene reconstructions. We show that very accurate camera calibration is needed to support this, and that such accurate calibration is difficult to achieve and maintain. We argue that for tasks like recognition, figure/ground separation is more important than 3D depth reconstruction, and demonstrate a stereo algorithm that supports figure/ground separation without 3D reconstruction.
dc.format	11 p.
dc.format	393745 bytes
dc.format	520870 bytes
dc.format	application/octet-stream
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-1435
dc.subject	stereo vision
dc.subject	camera calibration
dc.subject	noise sensitivity
dc.title	Why Stereo Vision is Not Always About 3D Reconstruction

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