Statistical Color Models with Application to Skin Detection

The existence of large image datasets such as the set of photos on the world wide web make it possible to build powerful generic models for low-level image attributes like color using simple histogram learning techniques. We describe the construction of color models for skin and non-skin classes from a dataset of nearly 1 billion labelled pixels. These classes exhibit a surprising degree of separability which we exploit by building a skin pixel detector achieving a detection rate of 80% with 8.5% false positives. We compare the performance of histogram and mixture models in skin detection and find histogram models to be superior in accuracy and computational cost. Using aggregate features computed from the skin detector we build a surprisingly effective detector for naked people. Our results suggest that color can be a powerful cue for detecting people in unconstrained imagery. We believe this work is the most comprehensive and detailed exploration of skin color models to date. Author email: fmjones,[email protected] c Compaq Computer Corporation, 1998 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of the Cambridge Research Laboratory of Compaq Computer Corporation in Cambridge, Massachusetts; an acknowledgment of the authors and individual contributors to the work; and all applicable portions of the copyright notice. Copying, reproducing, or republishing for any other purpose shall require a license with payment of fee to the Cambridge Research Laboratory. All rights reserved. CRL Technical reports are available on the CRL’s web page at http://www.crl.research.digital.com. Compaq Computer Corporation Cambridge Research Laboratory One Kendall Square, Building 700 Cambridge, Massachusetts 02139 USA