Presentation 1997/5/15
A Computational Model for Automatic Face Detection in Natural Scene Images using Color and Shape Information
Jean-Christophe Terrillon, Martin David, Shigeru Akamatsu,
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Abstract(in English) We use color and shape information for detecting and locating human faces in two-dimensional natural scene images. A color input image is first segmented using prespecified domains of hue and saturation that describe the color of human skin. After thresholding in hue and saturation, we group regions of the binarized image which have been classified as face candidates into a small number of clusters of connected pixels. We then implement a shape analysis by calculating moments for each cluster that are translation, scale and in-plane rotation invariant. In order to distinguish faces from distractors, a multilayer perceptron neural network is then used with the invariant moments as the input vector. Supervized learning of the network is implemented with the backpropagation algorithm, at first for frontal views of faces.
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Keyword(in English) Face detection / Color segmentation / Invariant moments / Neural networks
Paper # PRMU97-14
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Conference Information
Committee PRMU
Conference Date 1997/5/15(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Computational Model for Automatic Face Detection in Natural Scene Images using Color and Shape Information
Sub Title (in English)
Keyword(1) Face detection
Keyword(2) Color segmentation
Keyword(3) Invariant moments
Keyword(4) Neural networks
1st Author's Name Jean-Christophe Terrillon
1st Author's Affiliation ATR Human Information Processing Research Laboratories()
2nd Author's Name Martin David
2nd Author's Affiliation ATR Human Information Processing Research Laboratories
3rd Author's Name Shigeru Akamatsu
3rd Author's Affiliation ATR Human Information Processing Research Laboratories
Date 1997/5/15
Paper # PRMU97-14
Volume (vol) vol.97
Number (no) 40
Page pp.pp.-
#Pages 6
Date of Issue