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3D tracking between satellites using monocular computer vision
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005.
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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Stellenbosch : University of Stellenbosch
2009
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| _version_ | 1867614141145939968 |
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| access_status_str | Open Access |
| author | Malan, Daniel Francois |
| author2 | Steyn, W. H. |
| author_browse | Malan, Daniel Francois Steyn, W. H. |
| author_facet | Steyn, W. H. Malan, Daniel Francois |
| author_sort | Malan, Daniel Francois |
| collection | Thesis |
| dc_rights_str_mv | University of Stellenbosch |
| description | Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/3081 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:47:19.123Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2009 |
| publishDateRange | 2009 |
| publishDateSort | 2009 |
| publisher | Stellenbosch : University of Stellenbosch |
| publisherStr | Stellenbosch : University of Stellenbosch |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/3081 3D tracking between satellites using monocular computer vision Malan, Daniel Francois Steyn, W. H. Herbst, B. M. University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Computer vision Kalman filtering Theses -- Electrical and electronic engineering Dissertations -- Electrical and electronic engineering Kalman filtering Computer vision Electrical and Electronic Engineering Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. 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. 2009-05-22T09:13:48Z 2010-06-01T09:05:44Z 2009-05-22T09:13:48Z 2010-06-01T09:05:44Z 2005-03 Thesis http://hdl.handle.net/10019.1/3081 en University of Stellenbosch application/pdf Stellenbosch : University of Stellenbosch |
| spellingShingle | Computer vision Kalman filtering Theses -- Electrical and electronic engineering Dissertations -- Electrical and electronic engineering Kalman filtering Computer vision Electrical and Electronic Engineering Malan, Daniel Francois 3D tracking between satellites using monocular computer vision |
| title | 3D tracking between satellites using monocular computer vision |
| title_full | 3D tracking between satellites using monocular computer vision |
| title_fullStr | 3D tracking between satellites using monocular computer vision |
| title_full_unstemmed | 3D tracking between satellites using monocular computer vision |
| title_short | 3D tracking between satellites using monocular computer vision |
| title_sort | 3d tracking between satellites using monocular computer vision |
| topic | Computer vision Kalman filtering Theses -- Electrical and electronic engineering Dissertations -- Electrical and electronic engineering Kalman filtering Computer vision Electrical and Electronic Engineering |
| url | http://hdl.handle.net/10019.1/3081 |
| work_keys_str_mv | AT malandanielfrancois 3dtrackingbetweensatellitesusingmonocularcomputervision |