Eye detection in face images for a driver vigilance system

T. D’orazio, M. Leo, A. Distante
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引用次数: 25

Abstract

For a driver vigilance system one of the most important problems to be solved is eye detection. In this paper, we propose a new algorithm for eye detection that uses both iris geometrical information for determining in the whole image, the region candidate to contain an eye, and the symmetry for selecting the couple of eyes. The novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. After the first step, a validation algorithm based on a neural classifier has been applied to recognize if the couple of regions correspond effectively to eyes or false positives have been detected. Different experiments have been carried out on images of subjects with different eye colours, some of them wearing glasses. Tests showed robustness with respect to situations such as eyes partially occluded. In particular when applied to images where people have the eyes closed, the proposed algorithm correctly reveals the absence of eyes.
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面向驾驶员警戒系统的人脸图像眼睛检测
对于驾驶员警戒系统来说,眼睛检测是需要解决的最重要的问题之一。本文提出了一种新的眼睛检测算法,该算法利用虹膜几何信息在整个图像中确定包含眼睛的候选区域,并利用对称性选择一对眼睛。这项工作的新颖之处在于,该算法可以在复杂的图像上工作,不受背景、肤色分割等限制。在第一步之后,应用基于神经分类器的验证算法来识别这对区域是否有效地对应于眼睛或检测到假阳性。研究人员对不同眼睛颜色的受试者进行了不同的实验,其中一些人戴着眼镜。测试显示,在某些情况下,例如眼睛部分被遮挡的情况下,这种方法具有稳健性。特别是当应用于人们闭着眼睛的图像时,所提出的算法正确地揭示了眼睛的缺失。
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