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Titlebook: Audio- and Video-Based Biometric Person Authentication; Third International Josef Bigun,Fabrizio Smeraldi Conference proceedings 2001 Spri

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https://doi.org/10.1007/978-1-84628-671-1ion. Our method is based on the use of color and texture for searching skin-like regions in the images. This is accomplished with connected component analysis in adaptatively thresholded images. Multiple candidate regions appear, so determining whether each one corresponds or not to a face, solves t
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https://doi.org/10.1007/978-1-84628-671-1oor environment. The complete system contains two parts: the face locator and the face tracker. We will only describe the face locator. Face hypothesis are obtained combining a pyramidal greylevel template matching and a geometrical measure based on the facial feature organization. Classification to
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https://doi.org/10.1007/3-540-45344-X3D; Access Control; Audio; Authentication; Biometric Person Authentication; Face Recognition; Fingerprints
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978-3-540-42216-7Springer-Verlag Berlin Heidelberg 2001
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Face Identification and Verification via ECOChe training phase the client set is repeatedly divided into two ECOC specified sub-sets (super-classes) to train a set of binary classifiers. The output of the classifiers defines the ECOC feature space, in which it is easier to separate transformed patterns representing clients and impostors. As a
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