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Face Localization in 2D Frontal Face Images Using Luminosity Profiles Analysis

机译:使用光度轮廓分析的2D正面人脸图像中的人脸定位

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Face detection from a single image represents a challenging task because of variability in scale, location, orientation and pose. Facial expression, occlusion, and lighting conditions also change the overall appearance of faces. In this work we propose a fast face localization method in 2D frontal face images, through eyes detection, based on the analysis of the horizontal and vertical profiles of image's average luminosity and the definition of rules describing the relations between these profiles and the positions of characteristic face elements. Experimental results over the AR face database show high rates of successful detection together with reduced computational times that make this method particularly suitable for real time applications.
机译:由于尺寸,位置,方向和姿势的可变性,从单个图像进行面部检测是一项艰巨的任务。面部表情,遮挡和光照条件也会改变面部的整体外观。在这项工作中,我们在分析图像平均亮度的水平和垂直轮廓以及描述这些轮廓与特征位置之间关系的规则的定义的基础上,通过眼睛检测提出了一种二维正面图像中的快速面部定位方法面部元素。在AR人脸数据库上的实验结果表明,成功检测率很高,并且计算时间减少,这使得该方法特别适合于实时应用。

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