Abstract
We propose a method for an efficient frontal face detection using skin color, integrated feature space, and post processing. The proposed method reduces the search space by facial color information and detects face candidate windows by integrated feature space. The integrated feature space consists of intensity and texture information. Multiple Bayesian classifiers are employed for selection of face candidate windows on integrated feature space. And we use face and face-like nonface samples to training these Bayesian classifiers. Finally, face regions of the detected candidates are selected by merging and filtering post processing.
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© 2005 Springer-Verlag Berlin Heidelberg
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Nam, M.Y., Rhee, P.K. (2005). An Efficient Face Location Using Integrated Feature Space. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_43
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DOI: https://doi.org/10.1007/11552451_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28895-4
Online ISBN: 978-3-540-31986-3
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