基于独立成份分析和支持向量机的人眼注视研究  

Investigation of Eye Gaze Based on Independent Component Analysis and Support Vector Machine

作　　者：郑震[1] 张延炘[1] 胡颖新[1] 王建华[1] 常胜江[1] 

机构地区：[1]南开大学现代光学研究所,天津300071

出　　处：《光电子．激光》2007年第4期491-494,共4页Journal of Optoelectronics·Laser

摘　　要：采用独立成份分析(ICA)方法对单眼宽约为40 pixel的低分辨率人眼图像进行预处理,并把得到的一组组合系数输入支持向量机(SVM)判断图像中人眼的注视与否。对于单用户的注视探测,一维组合系数输入实现了100%的正确识别率;对于多用户的注视探测,二维组合系数输入实现了100%的正确率识别率。Different from the costly gazhing direction measurement and gazing tracking systems, the gazing detection system always uses low-resolution images to realize human-machine interaction. In this paper, the independent component analysis （ICA） is applied to preprocess the low-resolution （40-pixel wide of a single eye） eye images. After the processing,each eye image,which is represented by a low-dimensional vector,will serve as the input of Support Vector Machine（SVM） to give the judgment of gazing or not. The 1-dimensional and 2-dimensional vector input have achieved 100M classification rate to single-user and multi-user, respectively.

关 键 词：人眼 注视探知 独立成份分析(ICA) 支持向量机(SVM) 低维输入 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.4[自动化与计算机技术—控制科学与工程]