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Neural Network Cascade for Facial Feature Localization

机译:神经网络级联的面部特征定位

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We present here a complete system for the localization of facial features in frontal face images. In the first step, face detection is performed using Viola &: Jones state of art algorithm. Then, a cascade of neural networks localizes precisely 28 facial features. The first network performs a coarse detection of three areas in the image corresponding roughly to left and right eyes and mouths. Then, three local networks localize, in these areas, 9 key points per eye and 10 key points on the mouth. Thorough experiments on 3500 images from standard databases (Feret, BioID) show the detector accuracy, its generalization ability and speed.
机译:我们在这里提出了一个完整的系统,用于在正面人脸图像中定位人脸特征。第一步,使用Viola&:Jones最新技术算法执行面部检测。然后,级联的神经网络精确定位了28个面部特征。第一网络对图像中大致对应于左眼和右眼和嘴巴的三个区域执行粗略检测。然后,三个局域网在这些区域中将每只眼睛的9个关键点和嘴巴上的10个关键点本地化。对标准数据库(Feret,BioID)的3500张图像进行的全面实验显示了检测器的准确性,泛化能力和速度。

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