Face tracking based on grey prediction

Abstract

Although single skin color model is the normal method of face detection, it often has the disadvantages such as "ultra-detection" and bad real-time performance. This paper presents a new method of face tracking based on grey prediction model GM(1,1) combined with skin color model. The method uses grey prediction to minish the region of matching search for skin color model and the matching result to update the prediction basis of the grey model. In order to acquire the initial position of face, moving information of face is used, and the moving region is automatically acquired with information entropy. Compared to the α-β-γ filtering with assumption that object in image sequence makes uniformly accelerated motion, the experiment results of this method show that grey prediction model GM(1,1) can maintain minor error stably. The result of grey prediction is closer to the real motion trajectory, and better reflects the motion trend of face. It greatly enhances such two important indexes as robustness and real-time performance under the system tracking process.