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A pupil center detection algorithm based on eye color pixels differences

机译:一种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 Haarlike 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:本文介绍了一种新的瞳孔中心定位算法。使用基于Haarlike特征的级联分类器算法检测目标对象的面和眼睛。采用直方图均衡方法来增加图像对比度。我们的瞳孔中心检测的核心特征包括应用于眼睛区域图像上的自适应模板匹配过程,其集成了与瞳孔周围的区域的位置和颜色礼制相关的特定约束,以计算精确的瞳孔中心。实验结果通过评估瞳孔中心检测相对于地面真理参考的正确性来证明算法的效率。该程序将允许进一​​步发展一个系统,通过分析他们的眼球运动和将视觉注意力的关键区域转化为减轻他们的沟通的句子来促进受损人群的社会互动。

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