Video-based face detection and tracking technology has been widely applied in the fields of video surveillance, safe driving, human–computer interaction, and medical diagnosis. In video sequences, most existing face detection and tracking methods face interference caused by changes in ambient light, changes in human posture, and occlusion. To achieve accurate face tracking in video sequences, in this paper, we propose an efficient face detection and tracking framework for video sequences based
