Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Computing, Health and Science

School

Engineering and Mathematics

RAS ID

2044

Comments

This conference paper was originally published as: Phung, S. L., Chai, D. K., & Bouzerdoum, A. (2001). Skin colour based face detection. Proceedings of 7th Australian and New Zealand Intelligent Information Systems Conference. (pp. 0). Australia. IEEE. Original article available here

© 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Abstract

This paper describes a new approach to face detection. A colour input image is first processed using neural networks to detect skin regions in the image. Each neural network separates skin and non-skin pixels on the basis of chrominance information. The skin-colour classifier employs the committee machine technique, which improves skin colour detection by combining the classification results of a set of multilayer perceptrons (MLPs). The skin colour classifier achieves a classification rate of 84% compared to 81% for the best individual MLP classifier. The output of the committee machine is processed by a 2D smoothing filter before being converted into a binary map using a threshold. Finally, several post-processing techniques based on shape and luminance features are proposed for rejecting non-facial regions

DOI

10.1109/ANZIIS.2001.974071

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free_to_read

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Link to publisher version (DOI)

10.1109/ANZIIS.2001.974071