Since the late 1980’s when a concept of Neuromorphic Engineering was developed, many researchers from different fields, such as biology, physics, mathematics, computer science and engineering have been trying to design artificial neural systems whose physical architecture and design principles are based on those of biological nervous systems. One part of the research is developing an artificial vision system, a bio-inspired silicon retina which mimics some characteristics of the biological vision system. This type of imaging sensors have a huge potential to overcome some limitations of conventional vision sensors.
In this research, we aim to develop a visual SLAM system using a bio-inspired imaging sensor which can outperform state-of-the-art visual SLAM systems in a very efficient way.
Simultaneous Mosaicing and Tracking with an Event Camera
Hanme Kim, Ankur Handa, Ryad Benosman, Sio-Hoi Ieng, and Andrew J. Davison.
Proceedings of the British Machine Vision Conference (BMVC). BMVA Press, September 2014.
(Oral Presentation – 7.7% acceptance rate, Best Industry Paper).