Estimating optical flow with cellular neural networks

B. E. Shi, T. Roska, L. O. Chua

Research output: Contribution to journalArticle

Abstract

The cellular neural network is a locally interconnected neural network capable of high-speed computation when implemented in analog VLSI. This work describes a CNN algorithm for estimating the optical flow from an image sequence. The algorithm is based on the spatio-temporal filtering approach to image motion analysis and is shown to estimate the optical flow more accurately than a comparable approach proposed previously. Two innovative features of the algorithm are the exploitation of a biological model for hyperacuity and the development of a new class of spatio-temporal filter better suited for image motion analysis than the commonly used space-time Gabor filter.

Original languageEnglish
Pages (from-to)343-364
Number of pages22
JournalInternational Journal of Circuit Theory and Applications
Volume26
Issue number4
DOIs
Publication statusPublished - 1998

Keywords

  • CNN cellular neural network
  • Image motion analysis
  • Optical flow
  • VLSI

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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