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Principal component analysis for pigmentation distribution in whole facial image and prediction of the facial image in various ages

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In this paper, we apply principal component analysis to pigmentation distribution in whole face and obtain feature values. Furthermore, we estimate the relationship between the obtained vectors and the ages and simulate the changes of women facial image from in her 20s to in her any age by multiple regression analysis. Human faces is the well-known part which receive a lot of attention in the body. Changing the small quantity of the features in faces make large differences in their appearance. The features which we can receive divide broadly into two categories. One is the physical feature such as skin condition and its shape, and another one is the psychological features such as the ages and the health. In the beauty industry it is required to synthesize the skin texture based on the two kinds of the feature values. Previous works remain in the analysis of the skin texture using small area. By morphing shape of facial images to that of average face and extending the analyzed area to whole face, our method can analyze pigmentation distribution in whole face and simulate appearance of face by changing the age.
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Document Type: Research Article

Publication date: January 1, 2013

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

    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 paper for details.

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