Facial Feature Detection Using Conditional Regression Forests
Signal Processing and Communications Applications Conference(2015)
摘要
Even though there are many studies on facial feature detection from two dimensional still images, real-time facial feature detection is one of fresh fields. In this paper, a structure including Conditional Regression Forest and Local Zernike Moments is introduced to solve this problem. In this study, regression forests learn the relations between facial image patches and location of facial feature points conditional to head pose. This method is evaluated on Labeled Faces in the Wild (LFW) [2] database and promising results are obtained.
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关键词
Real-time Facial Feature Detection,Local Zernike Moments,Conditional Regression Forests
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