Dynamical Systems and Motion Vision

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6044

Full metadata record

DC Field	Value	Language
dc.creator	Heel, Joachim	-
dc.date	2004-10-04T14:36:47Z	-
dc.date	2004-10-04T14:36:47Z	-
dc.date	1988-04-01	-
dc.date.accessioned	2013-10-09T02:42:31Z	-
dc.date.available	2013-10-09T02:42:31Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1037	-
dc.identifier	http://hdl.handle.net/1721.1/6044	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	In this paper we show how the theory of dynamical systems can be employed to solve problems in motion vision. In particular we develop algorithms for the recovery of dense depth maps and motion parameters using state space observers or filters. Four different dynamical models of the imaging situation are investigated and corresponding filters/ observers derived. The most powerful of these algorithms recovers depth and motion of general nature using a brightness change constraint assumption. No feature-matching preprocessor is required.	-
dc.format	54 p.	-
dc.format	6308570 bytes	-
dc.format	2508040 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1037	-
dc.subject	dynamical systems	-
dc.subject	motion vision	-
dc.subject	Kalman filter	-
dc.subject	depth map	-
dc.subject	smotion recovery	-
dc.title	Dynamical Systems and Motion Vision	-
Appears in Collections:	MIT Items

Files in This Item:

There are no files associated with this item.

DSpace JSPUI