Biologically Inspired Visual Motion Detection in VLSI

Authors:
Ralph Etienne-Cummings
Affiliations:
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
Venue:
International Journal of Computer Vision
Year:
2001

Citing 8
Cited 1

Computing motion using analog VLSI vision chips: an experimental comparison among different approaches

International Journal of Computer Vision - Special issue: VLSI for computer vision
Distributed representation and analysis of visual motion

Distributed representation and analysis of visual motion
A general-purpose analog neural computer for real-time spatiotemporal pattern analysis: visual motion estimation

Fuzzy logic and neural network handbook
Motion Perception Using Analog VLSI

Analog Integrated Circuits and Signal Processing
Silicon retina with adaptive filtering properties

NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
An analog VLSI model of the fly elementary motion detector

NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
VLSI implementation of motion centroid localization for autonomous navigation

Proceedings of the 1998 conference on Advances in neural information processing systems II
Robot Vision

Robot Vision

A vision chip for color segmentation and pattern matching

EURASIP Journal on Applied Signal Processing

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Abstract

Visual motion detection is a fundament component of vision, and plays a vital role in scene analysis and understanding for behaving organisms. In computer vision, motion detection requires considerable resources to obtain real-time results. Very Large Scale Integration (VLSI) technology offers a convenient substrate upon which both photosensitive elements and motion extracting circuits can be implemented, thus allowing real-time motion detection. This paper presents two approaches for implementing real-time visual motion detection in VLSI. The two approaches mimic the two primary methods found in biological organisms. Insect motion detection employs local correlation and is implemented very close to the photoreceptors. In contrast, primate motion detection is performed in cortex, using spatiotemporally oriented neural filters. The analysis, construction and results of the hardware models of insect and primate visual motion detection are presented.