DETECTION OF FACIAL COMPONENTS IN A VIDEO SEQUENCE BY INDEPENDENT COMPONENT ANALYSIS

This paper presents two approaches for detecting facial components in the images contained in a video sequence by Independent Component Analysis (ICA). The ultimate objective is to map detected facial components such as eyes and mouth to a 3D wireframe model to be used in facial animation. One approach is to use face localization technique whereas the other deals with an entire image without cropping face part, but filtering with wavelet subband filters. Face localization is achieved by using the human skin color filtering in YCbCr subspace with other relevant facial information. The wavelet subband filter in the latter approach removes facial parts occupying a large area that contribute in ICA as large basis vectors. The method of Independent Component Analysis is then applied to identify main facial components for subsequent geometrical shape analysis.

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