Facial landmark detection and tracking with dynamically adaptive matched filters

A reliable method for the detection and tracking of facial landmarks in image sequences is presented. Given a set of prespecified facial landmarks in a reference face image, a bank of composite matched filters is constructed for reliable detection and accurate location of the landmarks in an input image sequence. The filter bank is dynamically adapted to each captured frame by learning from current and past landmark detections and considering geometrical modifications of the landmarks. The detected landmarks are accurately tracked using a kinematic motion model that predicts their coordinates in future frames. The performance of facial landmark detection and tracking obtained with the proposed method is tested by processing real-life image sequences. The obtained results are analyzed and discussed in terms of objective measures.