By Topic

Robust Bioinspired Architecture for Optical-Flow Computation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Guillermo Botella ; Dept. of Comput. Archit. & Autom., Complutense Univ. of Madrid, Madrid, Spain ; Antonio Garcia ; Manuel Rodriguez-Alvarez ; Eduardo Ros
more authors

Motion estimation from image sequences, called optical flow, has been deeply analyzed by the scientific community. Despite the number of different models and algorithms, none of them covers all problems associated with real-world processing. This paper presents a novel customizable architecture of a neuromorphic robust optical flow (multichannel gradient model) based on reconfigurable hardware with the properties of the cortical motion pathway, thus obtaining a useful framework for building future complex bioinspired real-time systems with high computational complexity. The presented architecture is customizable and adaptable, while emulating several neuromorphic properties, such as the use of several information channels of small bit width, which is the nature of the brain. This paper includes the resource usage and performance data, as well as a comparison with other systems. This hardware platform has many application fields in difficult environments due to its bioinspired nature and robustness properties, and it can be used as starting point in more complex systems.

Published in:

IEEE Transactions on Very Large Scale Integration (VLSI) Systems  (Volume:18 ,  Issue: 4 )