Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6044
Title: Dynamical Systems and Motion Vision
Keywords: dynamical systems
motion vision
Kalman filter
depth map
smotion recovery
Issue Date: 9-Oct-2013
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.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: AIM-1037
http://hdl.handle.net/1721.1/6044
Appears in Collections:MIT Items

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