CAJ | 학술논문

为提高视线方向计算精度,研制了一种基于立体视觉的视线追踪系统. 首先设计了一种可产生相邻2帧"亮暗瞳"图像的双摄像机红外光源,使用图像做差和椭圆拟合的方式计算瞳孔中心,结合在"暗瞳"图像中得到普洱钦斑中心,确定局部视线的盯视方向. 然后根据人类视线移动特点,提出使用神经网络结合卡尔曼滤波的方法进行瞳孔跟踪,用支持向量回归对人眼立体参数、局部视线盯视方向和盯视点之间的关系进行训练,得到视线映射模型. 实验结果表明,该系统能基本消除用户大范围头动的干扰.
위제고시선방향계산정도,연제료일충기우입체시각적시선추종계통. 수선설계료일충가산생상린2정"량암동"도상적쌍섭상궤홍외광원,사용도상주차화타원의합적방식계산동공중심,결합재"암동"도상중득도보이흠반중심,학정국부시선적정시방향. 연후근거인류시선이동특점,제출사용신경망락결합잡이만려파적방법진행동공근종,용지지향량회귀대인안입체삼수、국부시선정시방향화정시점지간적관계진행훈련,득도시선영사모형. 실험결과표명,해계통능기본소제용호대범위두동적간우.
To improve the calculative precision of gaze direction, an eye gaze tracking system using stereovision information is designed, it composes of two charge coupled device cameras and a novel loop illuminator. Pupil position is got through doing subtraction of the two adjacent images, "bright pupil" and "dark pupil", which are gained by difference between the Purkinje image in "dark pupil" and pupil center located by ellipse fitting. Pupil tracking is designed using neural network combined with Kalman filtering, and mapping model from 3D parameters to gaze point is worked out via support vector regression. Experiment proves that this system can most eliminate the interference