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Face recogniton based on the optimal combination of neural networks, eigenfaces and least squares matching methods

  • Report of a research project of the Fachhochschule Hannover, University of Applied Sciences and Arts, Department of Information Technologies. Automatic face recognition increases the security standards at public places and border checkpoints. The picture inside the identification documents could widely differ from the face, that is scanned under random lighting conditions and for unknown poses. The paper describes an optimal combination of three key algorithms of object recognition, that are able to perform in real time. The camera scan is processed by a recurrent neural network, by a Eigenfaces (PCA) method and by a least squares matching algorithm. Several examples demonstrate the achieved robustness and high recognition rate.

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Author:Werner Lechner
Document Type:Article
Year of Completion:2005
Publishing Institution:Hochschule Hannover
Release Date:2008/04/29
eigenface; face recognition
GND Keyword:Biometrie; Neuronales Netz; Künstliche Intelligenz
Link to catalogue:599626623
Institutes:Fakultät IV - Wirtschaft und Informatik
DDC classes:004 Informatik
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung 3.0