基于可见光源与独立成分分析法的实时人眼检测系统

提出一种基于特征与外貌混合检测确定人眼区域的实时人眼检测方法. 首先,依据可见光源在人眼角膜上反射形成耀点特性,通过图像处理算法提取潜在耀点位置,利用人眼几何特征的确定可能人眼候补区域;然后,提取人眼数据库中具有不同外貌特征的200幅人眼图像,采用FastICA算法估计出提取人眼图像的有效成分分析(ICA)基向量;最后,通过计算人眼候选区域在基向量上投影角度判断出左、右人眼区域准确位置. 实验结果表明,在人脸面部旋转、佩戴眼镜、大范围头部运动和不同光照强度下,实时人眼检测具有较高的检测正确率和较好的鲁棒性. 

A Real-Time Eye Detection System Based on Visible Light and Independent Components Analysis

A novel system for real-time eye detection with a hybrid eye detection method of appearance-based and feature-based was proposed. Firstly, the glints can be formed on the eye regions due to corneal reflection characteristics from the visible light. Potential glint regions were obtained based on image algorithm. According to the eye geometrical feature, the candidate eye regions can be extracted well. Secondly, 200 eye images with different appearance were extracted from the eye database. The basis vectors of independent components analysis (ICA) applied on those eye images were estimated based on the FastICA algorithm. Lastly, the accurate eye regions were detected by the projection angles from the candidate eye images to ICA basis vectors. The experimental results showed that the real-time eye detection has a better robustness and high correct rate to different face poses, with glasses, large head movement, and various illuminations.