Face Tracking

In many face recognition systems, the input is a video sequence consisting of one or more faces. It is necessary to track each face over this video sequence so as to extract the information that will be processed by the recognition system. Tracking is also necessary for 3D model-based recognition systems where the 3D model is estimated from the input video. Face tracking can be divided along different lines depending upon the method used, e.g., head tracking, feature tracking, image-based tracking, model-based tracking. The output of the face tracker can be the 2D position of the face in each image of the video (2D tracking), the 3D pose of the face (3D tracking), or the location of features on the face. Some trackers are able to output other parameters related to lighting or expression. The major challenges encountered by face tracking systems are robustness to pose changes, lighting variations, and facial deformations due to changes of expression, occlusions of the face to be tracked and clutter in the scene that makes it difficult to distinguish the face from the other objects.