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Based on a multi-step process, an automatic hair segmentation method is created and tested on a database of 115 manually segmented hair images. By extracting various information components from an image, including background color, face position, hair color, skin color, and skin mask, a heuristic-based method is created for the detection and segmentation of hair that can detect hair with an accuracy...
This paper proposes a novel method for the estimation of a person's skin-tone and under-tone by analyzing a large collection of photos of that person. By excluding badly lit images, and analyzing well-lit skin pixels, it becomes possible to compute an overall skin-tone estimate which is in-line with the person's true skin shade, and based on this, to determine a person's under-tone. Based on a study...
In this paper, we quantitatively evaluate the role of texture in hair patches, with a primary motivation of understanding what can be learned and applied by machine learning systems for texture-based hair detection. We evaluate the distribution of gradient directions in hair patches, and explore the relation between proximity to the face and the angle of the gradients for 2,870,000 hair patches selected...
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