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Proceedings Paper

Fixation-based filtering
Author(s): Thomas J. Olson; Robert J. Lockwood
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Paper Abstract

Fixation and visual attention are central themes in active vision research, and are closely related. In this paper we discuss one of several ways in which they interact. We describe filtering methods that allow an agent to selectively extract features of the object it is fixating and suppress features of foreground and background objects. The methods are essentially depth filters; they use disparity or motion information to suppress image features that are far from the fixation point in depth. They share a simple computational structure based on the Laplacian pyramid, and are readily amenable to hardware implementation. We present the filters and the properties of fixation geometry that allow them to work, and discuss their behavior. We present methods of implementing them in real time and describe ways of extending them to other features besides depth.

Paper Details

Date Published: 1 November 1992
PDF: 11 pages
Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); doi: 10.1117/12.131572
Show Author Affiliations
Thomas J. Olson, Univ. of Virginia (United States)
Robert J. Lockwood, Univ. of Virginia (United States)


Published in SPIE Proceedings Vol. 1825:
Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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