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Proceedings Paper

Robotic Attention Processing And Its Application To Visual Guidance
Author(s): Matthew Barth; Hirochika Inoue
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Paper Abstract

This paper describes a method of real-time visual attention processing for robots performing visual guidance. This robot attention processing is based on a novel vision processor, the multi-window vision system that was developed at the University of Tokyo. The multi-window vision system is unique in that it only processes visual information inside local area windows. These local area windows are quite flexible in their ability to move anywhere on the visual screen, change their size and shape, and alter their pixel sampling rate. By using these windows for specific attention tasks, it is possible to perform high speed attention processing. The primary attention skills of detecting motion, tracking an object, and interpreting an image are all performed at high speed on the multi-window vision system. A basic robotic attention scheme using the attention skills was developed. The attention skills involved detection and tracking of salient visual features. The tracking and motion information thus obtained was utilized in producing the response to the visual stimulus. The response of the attention scheme was quick enough to be applicable to the real-time vision processing tasks of playing a video 'pong' game, and later using an automobile driving simulator. By detecting the motion of a 'ball' on a video screen and then tracking the movement, the attention scheme was able to control a 'paddle' in order to keep the ball in play. The response was faster than that of a human's, allowing the attention scheme to play the video game at higher speeds. Further, in the application to the driving simulator, the attention scheme was able to control both direction and velocity of a simulated vehicle following a lead car. These two applications show the potential of local visual processing in its use for robotic attention processing.

Paper Details

Date Published: 22 March 1988
PDF: 11 pages
Proc. SPIE 0849, Automated Inspection and High-Speed Vision Architectures, (22 March 1988); doi: 10.1117/12.942842
Show Author Affiliations
Matthew Barth, University of California at Santa Barbara (United States)
Hirochika Inoue, University of Tokyo (Japan)

Published in SPIE Proceedings Vol. 0849:
Automated Inspection and High-Speed Vision Architectures
Rolf-Juergen Ahlers; Michael J. W. Chen, Editor(s)

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