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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Improved Statistical Techniques for Multi-part Face Detection and Recognition
verfasst von : Christian Micheloni, Enver Sangineto, Luigi Cinque, Gian Luca Foresti
Erschienen in: Image Analysis
Verlag: Springer Berlin Heidelberg
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In this paper we propose an integrated system for face detection and face recognition based on improved versions of state-of-the-art statistical learning techniques such as Boosting and LDA. Both the detection and the recognition processes are performed on facial features (e.g., the eyes, the nose, the mouth, etc) in order to improve the recognition accuracy and to exploit their statistical independence in the training phase. Experimental results on real images show the superiority of our proposed techniques with respect to the existing ones in both the detection and the recognition phase.