@inbook{799e96a3c4f049aa84dde9c3e95407e9,
title = "Multi-chip implementation of a biomimetic VLSI vision sensor based on the Adelson-Bergen algorithm",
abstract = "Biological motion sensors found in the retinas of species ranging from flies to primates are tuned to specific spatio-temporal frequencies to determine the local motion vectors in their visual field and perform complex motion computations. In this study, we present a novel implementation of a silicon retina based on the Adelson-Bergen spatio-temporal energy model of primate cortical cells. By employing a multi-chip strategy, we successfully implemented the model without much sacrifice of the fill factor of the photoreceptors in the front-end chip. In addition, the characterization results proved that this spatio-temporal frequency tuned silicon retina can detect the direction of motion of a sinusoidal input grating down to 10 percent contrast, and over more than a magnitude in velocity. This multi-chip biomimetic vision sensor will allow complex visual motion computations to be performed in real-time.",
author = "Erhan Ozalevli and Higgins, {Charles M.}",
year = "2003",
doi = "10.1007/3-540-44989-2_52",
language = "English (US)",
isbn = "3540404082",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "433--440",
editor = "Okyay Kaynak and Ethem Alpaydin and Erkki Oja and Lei Xu",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}