Abstract
M.Phil.
This work proposes a fast local image feature detector and descriptor that is im-
plementable on a GPU. The BFROST feature detector is the first published GPU
implementation of the popular FAST detector. A simple but novel method of feature orientation estimation which can be calculated in constant time is proposed.
The robustness and reliability of the orientation estimation is validated against rotation invariant descriptors such as SIFT and SURF. Furthermore, the BFROST
feature descriptor is robust to noise, scalable, rotation invariant, fast to compute
in parallel and maintains low memory usage. It is demonstrated that BFROST is
usable in real-time applications such as vision-based localization and mapping of
images captured from micro aerial platforms.