Pattern recognition problem rely upon the features inherent in the pattern of images. Face detection and recognition is one of the challenging research areas in the field of computer vision. In this paper, we present a method to identify skin pixels from still and video images using skin color. Face regions are identified from this skin pixel region. Facial features such as eyes, nose and mouth are then located. Faces are recognized from color images using an RBF based neural network. K means clustering algorithm is used to locate different facial elements. Orientation is corrected by using eyes. Parameters like inter eye distance, nose length, mouth position, Discrete Cosine Transform (DCT) coefficients etc. are computed and used for a Radial Basis Function (RBF) based neural network. This approach reliably works for face sequence with orientation in head, expressions etc.
机构:
Cornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14850 USA
Univ Tokyo, Dept Inf & Comm Engn, Tokyo, JapanCornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14850 USA
Yamasaki, Toshihiko
Chen, Tsuhan
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机构:
Cornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14850 USACornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14850 USA
Chen, Tsuhan
2012 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2012), VOL 2,
2012,
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579