Unsupervised and adaptive Gaussian skin-color model

In this article a segmentation method is described for the face skin of peo ple of any race in real time, in an adaptive and unsupervised way, based on a Gaussian model of the skin color (that will be referred to as Unsupervis ed and Adaptive Gaussian Skin-Color Model, UAGM). It is initialized by clus tering and it is not required that the user introduces any initial paramete rs. It works with complex color images, with random backgrounds and it is r obust to lighting and background changes. The clustering method used, based on the Vector Quantization (VQ) algorithm, is compared to other optimum mo del selection methods, based on the EM algorithm, using synthetic data. Fin ally, real results of the proposed method and conclusions are shown. (C) 20 00 Elsevier Science B.V. All rights reserved.