引用本文: | 陈叶飞,苏剑波.非学习模式下的类Haar特征快速人眼定位[J].控制理论与应用,2016,33(4):479~485.[点击复制] |
CHEN Ye-fei,SU Jian-bo.Fast eye localization without learning using Haar-like feature[J].Control Theory and Technology,2016,33(4):479~485.[点击复制] |
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非学习模式下的类Haar特征快速人眼定位 |
Fast eye localization without learning using Haar-like feature |
摘要点击 3383 全文点击 1866 投稿时间:2015-03-27 修订日期:2015-11-14 |
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DOI编号 10.7641/CTA.2016.50241 |
2016,33(4):479-485 |
中文关键词 人脸检测 人脸识别 眼睛定位 类Haar特征 |
英文关键词 face detection face recognition eye localization Haar-like feature |
基金项目 国家自然科学基金项目(61533012)资助. |
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中文摘要 |
本文研究非学习模式下的快速人眼定位算法. 首先, 在已检出的人脸区域中, 根据人脸几何特征的先验信
息, 设置一定的人眼候选区域, 通过高斯差分滤波消除光照影响. 其次, 定义一种类Haar的特征作用于二值化后的图
像, 在人眼候选区域计算该特征的评价值获得精确的人眼位置, 实现人眼的快速搜索定位. 该算法的处理方法简单
快速, 并且对于眼镜、眉毛以及发髻的干扰都有一定的鲁棒性. 算法通过人脸几何先验知识, 减少了训练和学习过
程. 实验结果表明, 该算法能够快速准确实时地完成眼睛的定位, 为后续的人脸识别提供必要的前提条件. |
英文摘要 |
This paper investigates the fast eye-localization algorithm without learning. First, in the detected face region,
we setup a certain eye candidate region according to the prior knowledge of the face geometry, and reduce the illumination
on it by using Gaussian difference filter. Next, we define a Haar-like feature to realize the fast eye localization on binary
image, and calculate the evaluation value for the eye candidate region to determine the accurate eye location. This method
we proposed is simple in computation and robust to the disturbances from eye glass frame, eye brow and hair. Because
this algorithm makes use of the prior knowledge of the face geometry, training and learning processes are thus reduced.
Experiments demonstrate that our method can localize eyes fast and accurately, providing the necessary condition for the
face recognition followed. |
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