Facial feature point location and tracking method based on improved Viola-Jones algorithm and Kalman filter prediction mechanism

Facial feature points positioning and tracking technology is an important research direction of human face in image processing, extensively apply in video monitoring, intelligent control, safety management and other aspects. It is through the analysis and processing of the face image, then automatically locate facial feature points in the current position, and with the feature point as the center to conduct real-time tracking [1-2]. The accuracy and real-time tracking and positioning are two important indexes to measure the effect of the algorithm in image processing, due to the large amount of data, so the effect of real-time positioning and tracking real-time performance. How to ensure the positioning accuracy and improve the real-time performance is important guarantee to realize the algorithm of reliability, and is the basis for human face feature point positioning and tracking of mature application.