FacialStereo: Facial depth estimation from a stereo pair

Consider the problem of sparse depth estimation from a given stereo image pair. This classic computer vision problem has been addressed by various algorithms over the past three decades. The traditional solution is to match the feature points in two images to estimate the disparity and therefore the depth. In this work, we consider a special case of scenes which have people with their front-on faces visible to the camera and we want to estimate how far a person is from the camera. This paper proposes a novel method to identify the depth of faces and even the depth of a single facial feature (eyebrows, eyes, nose, and lips) of a person from the camera using a stereo pair. The proposed technique employs active shape models (ASM) and face detection. ASM is a model-based technique consisting of a shape model which contains the data regarding the valid shapes of a face and a profile model which contains the texture of the face to localize the facial features in the stereo pair. We shall demonstrate how depth of faces can be obtained by the estimation of disparities from the landmark points.