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Face Detection with High Precision Based on Radial-Symmetry Transform and Eye-Pair Checking

机译：基于径向对称变换的高精度和眼对检查

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In this paper, a novel face detection algorithm is proposed which can detect both face and eye pupils efficiently at the same time. Interestingly, the results of face detection can be used to identify the regions of interest for pupil detection, and the results of pupil detection can be further contributed to detect more precise faces. A cascaded face filter is first constructed by using an adaboosting algorithm, which can rapidly filter out the non-face regions and keeps the possible face regions. Based on a radial-symmetry transform, the signal of eye pupil in a face candidate is considerably enhanced and becomes easy to detect. With an eye-pair checking process, the two pupil candidates are chosen as the outputted pupils if their corresponding face image obtains the highest verification score which is also larger than a predefined threshold. Experiments on the famous BioID face database have shown that 90. 0% of faces can be successfully detected, and among the detected faces about 98% of eye pupils are detected with highly acceptable precision.
机译：在本文中，提出了一种新的面部检测算法，其可以同时有效地检测面部和眼睛瞳孔。有趣的是，面部检测结果可用于识别瞳孔检测的感兴趣区域，并且可以进一步促进瞳孔检测的结果以检测更精确的面。首先通过使用ADABOOSTING算法构造级联面滤波器，该算法可以快速滤除非面积区域并保持可能的面部区域。基于径向对称变换，面部候选中的眼光瞳的信号显着提高，变得容易检测。通过对对检查过程，如果它们相应的面部图像获得也大于预定阈值的最高验证分数，则选择两个瞳孔候选者作为输出的瞳孔。着名的Bioid面部数据库的实验表明，可以成功检测到90％的面部，并且在检测到的面孔中，以高精度检测到约98％的眼睛瞳孔。

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