Statistical color models with application to skin detection
International Journal of Computer Vision
IEEE Computer Graphics and Applications
Color transfer in correlated color space
Proceedings of the 2006 ACM international conference on Virtual reality continuum and its applications
Interactive local adjustment of tonal values
ACM SIGGRAPH 2006 Papers
Light mixture estimation for spatially varying white balance
ACM SIGGRAPH 2008 papers
Enhancing photographs using content-specific image priors
Enhancing photographs using content-specific image priors
Towards race-related face identification: research on skin color transfer
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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This paper presents an efficient, personalizable and yet completely automatic algorithm for enhancing the brightness, tonal balance, and contrast of faces in thumbnails of online videos where multiple colored illumination sources are the norm and artifacts such as poor illumination and backlight are common. These artifacts significantly lower the perceptual quality of faces and skin, and cannot be easily corrected by common global image transforms. The same identifiable user, however, often uploads or participates in multiple photos, videos, or video chat sessions with varying illumination conditions. The proposed algorithm adaptively transforms the skin pixels in a poor illumination environment to match the skin color model of a prototypical face of the same user in a better illumination environment. It leaves the remaining non-skin portions of the image virtually unchanged while ascertaining a smooth, natural appearance. A component of our system automatically selects such a prototypical face for each user given a collection of uploaded videos/photo albums or prior video chat sessions by that user. We present several human rating studies on YouTube data that quantitatively demonstrate significant improvement in facial quality using the proposed algorithm.