DocumentCode :
53155
Title :
Bioinspired Visual Motion Estimation
Author :
Orchard, Garrick ; Etienne-Cummings, Ralph
Author_Institution :
Singapore Inst. for Neurotechnology (SINAPSE), Nat. Univ. of Singapore, Singapore, Singapore
Volume :
102
Issue :
10
fYear :
2014
fDate :
Oct. 2014
Firstpage :
1520
Lastpage :
1536
Abstract :
Visual motion estimation is a computationally intensive, but important task for sighted animals. Replicating the robustness and efficiency of biological visual motion estimation in artificial systems would significantly enhance the capabilities of future robotic agents. Twenty five years ago, in this very journal, Carver Mead outlined his argument for replicating biological processing in silicon circuits. His vision served as the foundation for the field of neuromorphic engineering, which has experienced a rapid growth in interest over recent years as the ideas and technologies mature. Replicating biological visual sensing was one of the first tasks attempted in the neuromorphic field. In this paper, we focus specifically on the task of visual motion estimation. We describe the task itself, present the progression of works from the early first attempts through to the modern day state-of-the-art, and provide an outlook for future directions in the field.
Keywords :
computer vision; elemental semiconductors; motion estimation; silicon; Carver Mead; Si; artificial systems; bioinspired visual motion estimation; biological processing; biological visual sensing; neuromorphic engineering; robotic agents; silicon circuits; AC-DC power converters; Biosensors; Motion estimation; Neural networks; Robot sensing systems; Velocity measurement; Very large scale integration; Visualization; Analog-digital integrated circuits; Analog-to-digital integrated circuits; image motion analysis; motion estimation; sensor systems; velocity measurement; very large scale integration;
fLanguage :
English
Journal_Title :
Proceedings of the IEEE
Publisher :
ieee
ISSN :
0018-9219
Type :
jour
DOI :
10.1109/JPROC.2014.2346763
Filename :
6891162
Link To Document :
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