A Robust Shape Reconstruction Method for Facial Feature Point Detection.
A Robust Shape Reconstruction Method for Facial Feature Point Detection.
复制标题
一种用于面部特征点检测的鲁棒形状重建方法
DOI：
10.1155/2017/4579398
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发表时间：
2017
影响因子：
--
通讯作者：
Huang Z
中科院分区：
文献类型：
--
作者：
Tan S;Chen D;Guo C;Huang Z
Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.
