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Circularity and self-similarity analysis for the precise location of the pupils

机译:学生精确位置的循环和自我相似性分析

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This paper presents a new method to automatically locate pupils in images (even with low-resolution) containing human faces. In particular pupils are localized by a two steps procedure: at first self-similarity information is extracted by considering the appearance variability of local regions and then they are combined with an estimator of circular shapes based on a modified version of the Circular Hough Transform. Experimental evidence of the effectiveness of the method was achieved on challenging databases containing facial images acquired under different lighting conditions and with different scales and poses.
机译:本文提出了一种新方法,可以自动定位在含有人面的图像中的学生(即使是低分辨率)。 特别地,瞳孔由两个步骤定位:通过考虑局部区域的外观可变性,提取第一自相似信息,然后基于圆形霍夫变换的修改版本与圆形的估计器组合。 对该方法有效性的实验证据是对挑战在不同照明条件下获得的面部图像和不同尺度和姿势的面部图像的具有挑战性的数据库。

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