Toward robust skin identification in video images

Abstract

There are many applications where it is desirable to segment a video image into regions defined by color. Among these are the recognition of gesture from the image (as opposed to instrumented gloves), facial expression and orientation, and video teleconferencing. In these examples, the important elements of the images are human hands and face, which share common skin coloration of the subject. This paper describes an approach to the identification of skin-colored regions of the image that is robust in terms of variations in skin pigmentation in a single subject, differences in skin pigmentation across a population of potential users, and subject clothing and image background. The paper also discusses the potential for being robust over a wide range of illuminating conditions.