A Fully Automatic Approach to Facial Feature Tracking Based on Image Registration

Xuetao Feng, Yangsheng Wang, Bin Ding, Xiaoyan Wang
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Abstract

This paper presents a real time, fully automatic facial feature detection and tracking approach. The head pose and facial action is tracked by a modified Candide 3D wireframe model based on an improved image registration technique. An effective model shape and position initialization method is also proposed. Experimental results demonstrate that our system is accurate, robust and fast enough for common applications, even when there are great pose and expression variations.
一种基于图像配准的全自动人脸特征跟踪方法
提出了一种实时、全自动的人脸特征检测与跟踪方法。基于改进的图像配准技术,采用改进的Candide三维线框模型跟踪头部姿态和面部动作。提出了一种有效的模型形状和位置初始化方法。实验结果表明,即使在姿势和表情变化很大的情况下,我们的系统也足够准确、鲁棒和快速。
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