Appearance-based Pain Recognition from Video Sequences

In this paper, we present an appearance-based approach for pain recognition from video sequences. An automatic face detector is employed which uses skin color modeling to detect human face in the video sequence. The pain affected portions of the face are obtained by using a mask image. The obtained face images are then projected onto a feature space, defined by eigen-faces, to produce the biometric template. Recognition is performed by projecting a new image onto the feature spaces spanned by the eigen-faces and then classifying the painful face by comparing its position in the feature spaces with the positions of known individuals. To check better accuracy, the system is tested against two more feature spaces defined by eigen-eyes and eigen-lips.