Affine-structure-based facial image encoding

A real-time algorithm for affine-structure-based video compression for facial images is presented. The face undergoing motion is segmented and triangulated to yield a set of control points. The set of control points generated by triangulation are tracked across a few frames using an intensity-based correlation technique. For accurate motion and structure estimation a Kalman-filter-based algorithm is used to track features on the facial image. The structure information of the control points is transmitted only during the bootstrapping stage. After that only the motion information is transmitted to the decoder. This reduces the number of motion parameters associated with control points in each frame. The local motion of the eyes and lips is captured using local 2-D affine transformations. For real time implementation a quad-tree based search technique is adopted to solve local correlation. Any remaining reconstruction error is accounted for using predictive encoding. Results on real image sequences demonstrate the applicability of the method