Robust face tracking using color segmentation aided with connected components labeling and morphology

Abstract

Based on a combination of color segmentation, connected components labeling and morphology, an algorithm for human face tracking and facial feature based head tilt angle extraction is developed. The method uses HSI space for color segmentation since in this space the dynamic range of the skin color is quite narrow thus enabling the differentiation of the face from other objects in the scene. The connected components labeling and morphology aid the segmentation process by removing noise artifacts in the scene and making the proposed algorithm robust to environmental conditions. The performance of the proposed system is evaluated for a large set of video sequences. It is found that the error in horizontal and vertical (x-, y-) translations, and the tilt angle is negligibly small for both studio and real environments.