Although local feature analysis(LFA) can solve that problem, the efficiency would decline to some extent when the location of feature points was not very accurate.
局部特征分析(LFA)可以提取人脸图像的局部特征,但由于人脸特征点定位不准确通常会导致系统性能下降。
参考来源 - 基于Gabor局部特征鉴别分析的人脸识别算法·2,447,543篇论文数据，部分数据来源于NoteExpress
We realize an algorithm based on minimum features for rapid face modeling from video, by tracking feature points, calibrating exterior parameter, estimating 3D location of feature points.
通过跟踪视频中的特征点，标定相机外参，进而估计特征点的3D位置，实现了基于一段视频中小特征点集的人脸建模算法。
The known error bound of location deviation is used to determine the minimum matching merit for two point pairs so that the effect of spurious feature points can be reduced.
基本思想是利用已知的最大定位误差，确定两点对的最小匹配度量，从而减小虚假特征点对匹配结果的影响。
Experiment results indicate that this approach can automatically locate the feature points, has obvious practicability in the way of feature location.
实验结果表明，该方法能自动定位特征点，在特征定位方面有很强的实用性。
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