A Novel Eye Localization Method With Rotation Invariance
A Novel Eye Localization Method With Rotation Invariance
复制标题
DOI：
10.1109/tip.2013.2287614
复制
发表时间：
2014
影响因子：
10.6
通讯作者：
Yan Ren;Shuang Wang;B. Hou;Jingjing Ma
中科院分区：
文献类型：
--
作者：
Yan Ren;Shuang Wang;B. Hou;Jingjing Ma
为了提高人脸处理算法的性能，本文提出了一种新的眼睛精确定位学习方法。现有的方法很少能同时在预测的眼睛区域、人脸图像和原始肖像中直接检测和定位任意角度的眼睛。为了在整个眼睛定位框架中保持旋转不变性，提出了一种不变性局部特征码本来表示眼睛模式。然后将2类稀疏表示分类器与金字塔型检测定位策略相结合，生成热图，完成判别分类和精确定位的任务。此外，采用一系列先验信息来提高定位精度和精度。在三个不同数据库上的实验结果表明，我们的方法能够有效地定位任意旋转情况下（平面360°）的眼睛。
This paper presents a novel learning method for precise eye localization, a challenge to be solved in order to improve the performance of face processing algorithms. Few existing approaches can directly detect and localize eyes with arbitrary angels in predicted eye regions, face images, and original portraits at the same time. To preserve rotation invariant property throughout the entire eye localization framework, a codebook of invariant local features is proposed for the representation of eye patterns. A heat map is then generated by integrating a 2-class sparse representation classifier with a pyramid-like detecting and locating strategy to fulfill the task of discriminative classification and precise localization. Furthermore, a series of prior information is adopted to improve the localization precision and accuracy. Experimental results on three different databases show that our method is capable of effectively locating eyes in arbitrary rotation situations (360° in plane).