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.
| Author: | Werner Lechner |
|---|---|
| URN: | urn:nbn:de:bsz:960-opus-470 |
| DOI: | https://doi.org/10.25968/opus-26 |
| Document Type: | Article |
| Language: | English |
| Year of Completion: | 2005 |
| Publishing Institution: | Hochschule Hannover |
| Release Date: | 2008/04/29 |
| Tag: | Gesichtserkennung 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): |  Creative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung 3.0 |
