Dynamical Systems and Motion Vision

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

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