Towards environmentally-invariant optic flow estimation inspired by insect biology /
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(Published version)
Date
2020
Authors
Skelton, Phillip Stanley Martin
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
thesis
Citation
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Abstract
Visual information is abundant and useful, not only for scene understanding, but also the estimation of motion. Biology has had millennia to develop visual systems, and many species rely heavily upon visual input for self-motion estimation in navigation. While biologists continue to further the understanding of these complex systems, technologists have fallen behind in the application of this knowledge. Concentrating on the motion processing pathways of insects, my research links biologically-inspired signal processing techniques to applications that are technologically viable. Levels of accuracy and consistency previously unseen in dense motion estimators were achieved while transferring existing biological knowledge into a technological application. New biological insights were gained, and their implementation has resulted in a plethora of new opportunities for autonomous navigation.
School/Discipline
University of South Australia. Defence and Systems Institute.
Defence and Systems Institute.
Defence and Systems Institute.
Dissertation Note
Thesis (PhD(Systems Engineering))--University of South Australia, 2020.
Provenance
Copyright 2020 Phillip Stanley Martin Skelton.
Description
1 ethesis (xxiv, 219 pages) :
illustrations (some colour), charts (some colour)
Includes bibliographical references (pages 157-194)
illustrations (some colour), charts (some colour)
Includes bibliographical references (pages 157-194)
Access Status
506 0#$fstar $2Unrestricted online access