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.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/3081 |
Date | 03 1900 |
Creators | Malan, Daniel Francois |
Contributors | Steyn, W. H., Herbst, B. M., University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. |
Publisher | Stellenbosch : University of Stellenbosch |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Rights | University of Stellenbosch |
Page generated in 0.0014 seconds