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A pupil center detection algorithm based on eye color pixels differences

机译:基于眼睛颜色像素差异的瞳孔中心检测算法

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In this paper we present a new algorithm for pupil center localization. The face and eyes of the target subject are detected using the Cascade Classifier algorithm based on Haar-like features. A histogram equalization method is employed to increase image contrast. The core feature of our pupil center detection consists of an adaptive template matching procedure applied on the eye region image that integrates specific constraints related to location and color proprieties of areas surrounding the pupil in order to compute the precise pupil center. Experimental results demonstrate the efficiency of the algorithm by assessing the correctness of the pupil center detection with respect to a ground truth reference. This procedure will allow further development of a system that facilitates social interaction of impaired people by analyzing their eye movements and translating key zones of visual attention focus into sentences that alleviate their communication.
机译:在本文中,我们提出了一种用于瞳孔中心定位的新算法。使用基于Haar样特征的Cascade分类器算法检测目标对象的面部和眼睛。直方图均衡方法用于增加图像对比度。我们的瞳孔中心检测的核心功能包括应用于眼睛区域图像的自适应模板匹配程序,该程序整合了与瞳孔周围区域的位置和颜色特性有关的特定约束,以便计算出精确的瞳孔中心。实验结果通过评估相对于地面真实基准的瞳孔中心检测的正确性,证明了该算法的有效性。此程序将允许进一​​步开发一种系统,该系统通过分析残障人士的眼动并将视力关注重点的关键区域转换为减轻其沟通能力的句子,从而促进残障人士的社交互动。

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