Neural network target tracker

Chiewcharn Narathong; Rafael M. Inigo

doi:10.1117/12.21161

1 August 1990 Neural network target tracker

Chiewcharn Narathong, Rafael M. Inigo

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21161
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

Real-time visual tracking is a difficult problem requiring high speed processing. We have previously reported a fast tracking algorithm (the Line Correlator Tracker (LCT) )12 capable of estimating displacement for a sequence of images using a conventional rectangular sensor. When used with a logarithmic-spiral sensor3, changes of scale can also be estimated. Although the algorithm can be implemented using sequential or parallel digital processing, a Hopfield-Tank (HT) network implementation is potentially simpler and faster.

Citation Download Citation

Chiewcharn Narathong and Rafael M. Inigo "Neural network target tracker", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21161

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