NDLI: Hardware implementation of a visual-motion pixel using oriented spatiotemporal neural filters

Content Provider	IEEE Xplore Digital Library
Author	Etienne-Cummings, R. Van der Spiegel, J. Mueller, P.
Copyright Year	1992
Abstract	A pixel for measuring two-dimensional (2-D) visual motion with two one-dimensional (1-D) detectors has been implemented in very large scale integration. Based on the spatiotemporal feature extraction model of Adelson and Bergen, the pixel is realized using a general-purpose analog neural computer and a silicon retina. Because the neural computer only offers sum-and-threshold neurons, the Adelson and Bergen's model is modified. The quadratic nonlinearity is replaced with a full-wave rectification, while the contrast normalization is replaced with edge detection and thresholding. Motion is extracted in two dimensions by using two 1-D detectors with spatial smoothing orthogonal to the direction of motion. Analysis shows that our pixel, although it has some limitations, has much lower hardware complexity compared to the full 2-D model. It also produces more accurate results and has a reduced aperture problem compared to the two 1-D model with no smoothing. Real-time velocity is represented as a distribution of activity of the 18 X and 18 Y velocity-tuned neural filters.
Sponsorship	IEEE Circuits and Systems Society
Starting Page	1121
Ending Page	1136
Page Count	16
File Size	454813
File Format	PDF
ISSN	10577130
Volume Number	46
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-09-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hardware Motion detection Detectors Smoothing methods Motion measurement Two dimensional displays Very large scale integration Spatiotemporal phenomena Feature extraction Analog computers
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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