Facial feature point tracking of active appearance model based on prediction of strong tracking filter

Abstract

Active Appearance Model(AAM) can locate facial feature points of video sequences.When the initial position is far away from the destination,the fitting process often falls into local minimum,so that the iteration cannot converge to the correct location,resulting in locating failure.Concerning this problem,a facial feature point tracking method of AAM using prediction of strong tracking filter(STF-AAM) was proposed.Firstly,it viewed the head movement in the video as a dynamic system and used Strong Tracking Filter(STF) to predict and track it.So the fitting initial position of each frame was found and fitting algorithm was executed.This method could find the fitting initial position of each frame of video sequences and achieve a more accurate and more rapid tracking result.The experimental results show that the proposed method performs better than the traditional method in the tracking speed along with the fitting accuracy.