高技术通讯2011，Vol.21Issue(4)：333-338,6.DOI:10.3772/j.issn.1002-0470.2011.04.001
基于混合特征的注视方向判别
Monocular gaze estimation based on hybrid feature
摘要
Abstract
This paper proposes a method for gaze estimation based on the hybrid feature which comprises the model-based feature and the appearance-based feature. The Model-based feature is the vectors between the located marks of couple eyes.The appearance-based feature is the directional binary pattern (DBP), which treats an eye image as a high-dimension feature。 This article uses the support vector regression (SVR) to rank the hybrid feature, which maps a gaze direction with the frontal head pose. In the person-independent experiment, the dataset for training SVR included 4089 samples of 11 persons. In collecting the training data, the subject faced a camera within a frontal head pose and gazed the pre-defined points on the screen. In the real-time experiment, only one camera was used. The input was a captured picture and the output was the Euler angles with respect to the camera coordinate system. The experimental results showed that the proposed method was efficient and the accuracy is around 3°.关键词
视线跟踪/混合特征/表观特征/模型特征/支持向量回归(SVR)Key words
gaze estimation/ hybrid feature/ appearance-based feature/ model-based feature/ support vector regression (SVR)引用本文复制引用
葛宏志,陈熙霖..基于混合特征的注视方向判别[J].高技术通讯,2011,21(4):333-338,6.基金项目
863计划(2009AA01Z317),国家自然科学基金(60603023)和北京市自然科学基金(4061001)资助项目. （2009AA01Z317）
