Reconfigurable biologically inspired visual motion systems using modular neuromorphic VLSI Chips

Erhan Özalevli, Charles M. Higgins

Research output: Contribution to journalArticle

28 Scopus citations

Abstract

Visual motion information provides a variety of clues that enable biological organisms from insects to primates to efficiently navigate in unstructured environments. We present modular mixed-signal very large-scale integration (VLSI) implementations of the three most prominent biological models of visual motion detection. A novel feature of these designs is the use of spike integration circuitry to implement the necessary temporal filtering. We show how such modular VLSI building blocks make it possible to build highly powerful and flexible vision systems. These three biomimetic motion algorithms are fully characterized and compared in performance. The visual motion detection models are each implemented on separate VLSI chips, but utilize a common silicon retina chip to transmit changes in contrast, and thus four separate mixed-signal VLSI designs are described. Characterization results of these sensors show that each has a saturating response to contrast to moving stimuli, and that the direction of motion of a sinusoidal grating can be detected down to less than 5% contrast, and over more than an order of magnitude in velocity, while retaining modest power consumption.

Original languageEnglish (US)
Pages (from-to)79-92
Number of pages14
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Volume52
Issue number1
DOIs
StatePublished - Jan 1 2005

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Keywords

  • Address-event representation (AER)
  • Analog very large-scale integration (VLSI)
  • Biomimetic
  • Modular
  • Neuromorphic
  • Visual motion

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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