Identity verification through the fusion of face and speaker data

John G. Keller; Steven K. Rogers; Dennis W. Ruck; Mark E. Oxley

doi:10.1117/12.170010

2 March 1994 Identity verification through the fusion of face and speaker data

John G. Keller, Steven K. Rogers, Dennis W. Ruck, Mark E. Oxley

Proceedings Volume 2243, Applications of Artificial Neural Networks V; (1994) https://doi.org/10.1117/12.170010
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Two verification systems, face and speaker, are fused to form a single identity verification system. The Karhunen-Loeve Transform (KLT) is used for dimensional reduction, and a back- propagation neural net is used for classification. Verification involved training a net for each individual in the database for two classes of outputs, `Joe' or `not Joe.' The base speaker identification system used Cepstral analysis for feature extraction and a distortion measure for classification. Verification in this case involved performing the KLT on the Cepstral coefficients and then classifying using a two-class neural net for each individual. KLT feature reduction is compared to alternative linear methods, and the KLT is found to provide superior performance. The fusion of the two base verification systems is shown to provide superior performance over either system alone.

Citation Download Citation

John G. Keller, Steven K. Rogers, Dennis W. Ruck, and Mark E. Oxley "Identity verification through the fusion of face and speaker data", Proc. SPIE 2243, Applications of Artificial Neural Networks V, (2 March 1994); https://doi.org/10.1117/12.170010

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