Skelton, Phillip Stanley Martin2025-12-172025-12-172020https://hdl.handle.net/11541.2/1448871 ethesis (xxiv, 219 pages) :illustrations (some colour), charts (some colour)Includes bibliographical references (pages 157-194)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.enoptic flow;biologically inspired;biology;insect vision;computer visionImage processingInsectsMotion perception (Vision)Visual evoked response.thesis