Authors:
J. F. Lichtenauer
;
M. J. T. Reinders
and
E. A. Hendriks
Affiliation:
Information & Communication Theory Group, Delft University of Technology, Netherlands
Keyword(s):
Adaptive color modelling, chrominance, chromatic color space, skin detection.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Illumination and Reflectance Modeling
;
Image Formation and Preprocessing
Abstract:
In case of the absence of a calibration procedure, or when there exists a color difference between direct and ambient light, standard chrominance models are not completely brightness invariant. Therefore, they cannot provide the best space for robust color modeling. Instead of using a fixed chrominance model, our method estimates the actual dependency between color appearance and brightness. This is done by fitting a linear function to a small set of color samples. In the resulting self-calibrated chromatic space, orthogonal to this line, the color distribution is modeled as a 2D Gaussian distribution. The method is applied to skin detection, where the face provides the initialization samples to detect the skin of hands and arms. A comparison with fixed chrominance models shows an overall improvement and also an increased reliability of detection performance in different environments.