Explicit Skin Reflectance Modeling for Improved Skin Segmentation and Illuminant Color Estimation The segmentation of skin regions in images is an important pre-
processing
step for many computer vision applications like face detection, face
tracking or image retrieval systems. However, skin processing using
color
information can be a challenging task as the appearance of the skin in
images is affected by different factors such as illumination, environment
and
ethnicity. The aim of this project is the analysis of the interaction of
light with human skin from computer vision's perspective. The objective
is
the adaptation of state-of-the-art skin reflectance models to better suit
computer vision related applications. Therein, two major parts have to be
addressed: physics-based skin detection and illumination estimation
based on the detected skin. Both aspects are highly correlated, as
changes in the spectrum of the reflected light can be either due to a
different skin albedo, or due to a change in the illumination. Illumination
compensation can be
used to enhance skin detection algorithms. Conversely, one can use
previously detected skin regions to estimate the illuminant. | Project manager: Elli Angelopoulou, Ph.D., Akad. Rat
Project participants: Dipl.-Inf. Eva Eibenberger
Keywords: reflectance; skin detection; illuminant color estimation
Duration: 1.8.2009 - 30.9.2013
Sponsored by: International Max-Planck Research School (IMPRS)
Contact: Eibenberger, Eva E-Mail: eva.eibenberger@fau.de
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