A Neural Network Approach to Tracking Eye Position
A Neural Network Approach to Tracking Eye Position
复制标题
跟踪眼睛位置的神经网络方法
DOI：
10.1207/s15327590ijhc0901_4
复制
发表时间：
1997
期刊：
影响因子：
--
通讯作者：
D. Eichmann
中科院分区：
文献类型：
--
作者：
B. Wolfe;D. Eichmann
提出了基于神经网络的眼动仪的设计。一系列反向传播神经网络实验通过具有多个获胜隐藏层节点的增强前馈神经网络将合成视频图像转换为眼睛坐标。讨论了设计过程中遇到的困难。结果表明，通过处理从安装在护目镜上的微型电荷耦合器件（CCD）相机收集的视频图像，可以精确、细粒度地跟踪人眼位置。
The design of a neural network based eye tracker is presented. A series of experiments with counterpropagation neural networks convert synthetic video images into eye coordinates by an enhanced feed-forward neural network with multiple winning hidden layer nodes. Difficulties encountered during the design process are discussed. The results show that accurate, fine-grained tracking of a human's eye position is possible by processing the video image collected from a goggle-mounted miniature charge-coupled device (CCD) camera.