Visual Grouping by Neural Oscillator Networks
Name
Yu-2009-Visual Grouping by N.pdf
Size
3 MB
Format
Adobe PDF
Checksum (MD5)
d8e1d766c6667b893fc36ecb666640be
Author(s)
Yu, Guoshen
Slotine, Jean-Jacques E.
Date Issued
December 2009
Journal
IEEE Transactions on Neural Networks
Publisher
Institute of Electrical and Electronics Engineers
Citation
Guoshen Yu, and J.-J. Slotine. “Visual Grouping by Neural Oscillator Networks.” Neural Networks, IEEE Transactions on 20.12 (2009): 1871-1884. © 2009 IEEE
Version
Final published version
Abstract
Distributed synchronization is known to occur at several scales in the brain, and has been suggested as playing a key functional role in perceptual grouping. State-of-the-art visual grouping algorithms, however, seem to give comparatively little attention to neural synchronization analogies. Based on the framework of concurrent synchronization of dynamical systems, simple networks of neural oscillators coupled with diffusive connections are proposed to solve visual grouping problems. The key idea is to embed the desired grouping properties in the choice of the diffusive couplings, so that synchronization of oscillators within each group indicates perceptual grouping of the underlying stimulative atoms, while desynchronization between groups corresponds to group segregation. Compared with state-of-the-art approaches, the same algorithm is shown to achieve promising results on several classical visual grouping problems, including point clustering, contour integration, and image segmentation.
Subjects
vision
synchronization
neural oscillator
image segmentation
Grouping
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1109/tnn.2009.2031678
