Temporal object identification via fuzzy models

James M. Keller; Jeffrey Osborn

doi:10.1117/12.57083

1 February 1992 Temporal object identification via fuzzy models

James M. Keller, Jeffrey Osborn

Proceedings Volume 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques; (1992) https://doi.org/10.1117/12.57083
Event: Robotics '91, 1991, Boston, MA, United States

Abstract

In designing systems which analyze temporal sequences of images, it is necessary to provide mechanisms which identify, track, and release objects over time. There is considerable uncertainty in the definition of objects in a natural scene as evidenced, for example, in forward looking infrared (FLIR) imagery. In this paper, we present a methodology, based on the theory of fuzzy sets, which can handle this problem. It contains a feature driven fuzzy correlator which integrates current and past information to update object histories, to detect new objects, and to determine when objects leave the scene. The intention is to use such a system in a surveillance mode, where there is reasonable time for computation. Examples are given from an automatic target recognition application.

Citation Download Citation

James M. Keller and Jeffrey Osborn "Temporal object identification via fuzzy models", Proc. SPIE 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques, (1 February 1992); https://doi.org/10.1117/12.57083

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