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FPGA Acceleration of Multilevel ORB Feature Extraction for Computer Vision

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thesis
posted on 29.06.2018 by JOSHUA ADAM WEBERRUSS
This work accelerates robotic vision processing using specialised low cost, low power and high performance digital design. The design approach exploits fine grain parallelism available to hardware designs on Field Programmable Gate Arrays. State of the art image features are extracted at high frame rates, even for high definition video, allowing real time robot localisation and mapping from single or multiple cameras on mobile devices and robots. The PhD validates the approach and shows it is much faster than software implementations on conventional or graphics processors with a real time demonstration.

History

Campus location

Australia

Principal supervisor

Lindsay Kleeman

Additional supervisor 1

Tom Drummond

Year of Award

2018

Department, School or Centre

Electrical and Computer Systems Engineering

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Engineering

Exports

Exports