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Proceedings Paper

Tracking image features using a parallel computational model
Author(s): Timothy J. Ellis; Majid Mirmehdi; Geoff R. Dowling
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Paper Abstract

This paper describes a parallel implementation of an image feature tracking system. The system is designed to operate as the front-end of a vision system for controlling autonomous guided vehicles (AGV). Image features or tokens (edge-based line segments in the example given here) are extracted from the image and allocated to individual tracking processes. Both the extraction and the tracking stages are performed by concurrent processes. Arbitrary tracking algorithms may be associated with each process. In the current implementation, a Kalman filter is used to track and predict tokens in subsequent image frames.

Paper Details

Date Published: 1 March 1992
PDF: 12 pages
Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58571
Show Author Affiliations
Timothy J. Ellis, City Univ. (United Kingdom)
Majid Mirmehdi, City Univ. (United Kingdom)
Geoff R. Dowling, City Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 1708:
Applications of Artificial Intelligence X: Machine Vision and Robotics
Kevin W. Bowyer, Editor(s)

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