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Adapting A Statistical Skin Colour Model To Illumination Changes

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Skin colour segmentation is important for human face tracking. An often used approach is to approximate the skin chromaticity distribution with a statistical model, e.g. with the distribution's covariance matrix. The advantage of this approach is that it is invariant to size and orientation and fast to compute. A disadvantage is that it is sensitive to changes of the illumination colour.

This paper investigates how accurately the covariance matrix of facial skin chromaticity distributions might be modelled for different illumination colours using a physics-based approach. Results are presented using real image data taken under different illumination colours and from subjects with different shades of skin. The eigenvectors of the modelled and measured covariances deviate in orientation about 4o. This seems to be within a useful range for skin colour segmentation, and hence allow the statistical model to adapt to illumination changes.
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Document Type: Research Article

Publication date: January 1, 2002

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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