3D tracking between satellites using monocular computer vision

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dc.contributor.advisor Steyn, W. H. en_ZA
dc.contributor.advisor Herbst, B. M. en_ZA
dc.contributor.author Malan, Daniel Francois en_ZA
dc.contributor.other University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
dc.date.accessioned 2009-05-22T09:13:48Z en_ZA
dc.date.accessioned 2010-06-01T09:05:44Z
dc.date.available 2009-05-22T09:13:48Z en_ZA
dc.date.available 2010-06-01T09:05:44Z
dc.date.issued 2005-03
dc.identifier.uri http://hdl.handle.net/10019.1/3081
dc.description Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005.
dc.description.abstract Visually estimating three-dimensional position, orientation and motion, between an observer and a target, is an important problem in computer vision. Solutions which compute threedimensional movement from two-dimensional intensity images, usually rely on stereoscopic vision. Some research has also been done in systems utilising a single (monocular) camera. This thesis investigates methods for estimating position and pose from monocular image sequences. The intended future application is of visual tracking between satellites flying in close formation. The ideas explored in this thesis build on methods developed for use in camera calibration, and structure from motion (SfM). All these methods rely heavily on the use of different variations of the Kalman Filter. After describing the problem from a mathematical perspective we develop different approaches to solving the estimation problem. The different approaches are successfully tested on simulated as well as real-world image sequences, and their performance analysed. en_ZA
dc.language.iso en en_ZA
dc.publisher Stellenbosch : University of Stellenbosch
dc.subject Computer vision en_ZA
dc.subject Kalman filtering en_ZA
dc.subject Theses -- Electrical and electronic engineering en_ZA
dc.subject Dissertations -- Electrical and electronic engineering en_ZA
dc.subject.lcsh Kalman filtering en_ZA
dc.subject.lcsh Computer vision en_ZA
dc.subject.other Electrical and Electronic Engineering en_ZA
dc.title 3D tracking between satellites using monocular computer vision en_ZA
dc.type Thesis en_ZA
dc.rights.holder University of Stellenbosch
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