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A feature and appearance based method for eye detection on gray intensity face images

机译:基于特征和外观的灰度强度人脸图像眼睛检测方法

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This paper presents a robust and precise eye detection algorithm on gray intensity face images. Our method combines the strength of two existing methods which are a feature based method and an appearance based method to detect and locate a precise pupil center. It includes the following three steps. First, the feature based method is used. The method uses a projection function to detect all possible regions of each left and right eye. Second, the appearance based method is used to filter out all non eye regions, and keep only one region for each left and right eye. All possible regions will go through a Principal Component Analysis (PCA). Third, a modified hybrid projection function is used to locate the pupil center for both eyes. The experimental results show that the proposed method has an efficient performance with the accuracy of more than 90.52%.
机译:本文提出了一种对灰度强度的人脸图像的鲁棒和精确的眼睛检测算法。我们的方法结合了两种现有方法的优势,这两种方法是基于特征的方法和基于外观的方法,用于检测和定位精确的瞳孔中心。它包括以下三个步骤。首先,使用基于特征的方法。该方法使用投影功能来检测每只左眼和右眼的所有可能区域。其次,基于外观的方法用于过滤掉所有非眼睛区域,并且每只左眼和右眼仅保留一个区域。所有可能的区域都将通过主成分分析(PCA)。第三,改进的混合投影功能用于定位两只眼睛的瞳孔中心。实验结果表明,该方法具有较高的效率,准确率高达90.52%。

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