Document Type
Article
Publication Date
5-2012
Abstract
A qualia exploitation of sensor technology (QUEST) motivated architecture using algorithm fusion and adaptive feedback loops for face recognition for hyperspectral imagery (HSI) is presented. QUEST seeks to develop a general purpose computational intelligence system that captures the beneficial engineering aspects of qualia-based solutions. Qualia-based approaches are constructed from subjective representations and have the ability to detect, distinguish, and characterize entities in the environment Adaptive feedback loops are implemented that enhance performance by reducing candidate subjects in the gallery and by injecting additional probe images during the matching process. The architecture presented provides a framework for exploring more advanced integration strategies beyond those presented. Algorithmic results and performance improvements are presented as spatial, spectral, and temporal effects are utilized; additionally, a Matlab-based graphical user interface (GUI) is developed to aid processing, track performance, and to display results.
Source Publication
Advances in Artificial Intelligence
Recommended Citation
David M. Ryer, Trevor J. Bihl, Kenneth W. Bauer, Steven K. Rogers, "QUEST Hierarchy for Hyperspectral Face Recognition", Advances in Artificial Intelligence, vol. 2012, Article ID 203670, 13 pages, 2012. https://doi.org/10.1155/2012/203670
Comments
Copyright © 2012 US Government work not protected by copyright laws.
This is an open access article published by and distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CC BY 3.0
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