三维注视点的建模和隐式标定方法研究

项目名称： 三维注视点的建模和隐式标定方法研究

项目编号： No.61302191

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 张远辉

作者单位： 中国计量学院

项目金额： 26万元

中文摘要： 注视点即人类视觉注意的空间位置所在，它是获取心理认知信息、实现自然的人机交互的重要渠道。目前，注视点图像视频法基于视力正常人群建立，不具普适性；且现有的方法存在较多弊端，未能同时满足标定操作便捷、支持头部运动、空间定位精度高等要求。本项目首先扩展Gullstrand眼球模型，建立一个通用的适合不同角膜曲率、不受畸变和折射影响，且支持3D到3D定位的注视点模型；开展三维视觉显著场研究，应用贝叶斯学习方法对注视点模型进行隐式参数标定，并通过空间视觉敏感特征分析渐进修正以提高精度；根据双眼运动同步特征及Listing定律构建眼球图像运动方程，依靠数据关联和轨迹滤波等技术消除图像噪声对目标定位的干扰。本项目旨在拓展注视点研究的人群适用范围和应用领域，实现标定操作、跟踪精度和视觉抗干扰等相关性能的优化。项目有望为注视点建模、标定和图像特征跟踪提供新的研究思路和解决方案，并完善相关理论。

中文关键词： 注视点；可视化调试器；滤波；参数估计；投票算法

英文摘要： Point of gaze is the position where human visual attention locates, it is an important channel for obtaining cognitive information or implementing natural human computer interaction. Currently, video-oculography methods are constructed based on the population with normal vision,thus it does not have much suitability. Existing methods have some disadvantages, they fail to meet all the requirements for convenient operation, large-scale head movements and high spatial accuracy. This project firstly extends the Gullstrand eye model by establishing a general model to handle different cornea curvatures, distortions and refractions. The general model supports 3D to 3D point of gaze localization. Next, a 3D saliency field is analyzed, the Bayesian learning method is used to implicitly calibrate the model's parameters. The spatial saliency features are analyzed to progressively correct the errors and improve accuracy. Thirdly, motion equations are built according to the synchronization features of the eye movements and the Listing law, methods in data association and trajectory filtering are applied to eliminate the image noise interferences in target localization. This project aims to expand the scope of target population and applications, to achieve performance optimization in calibration, tracking and anti-interferenc

英文关键词： gaze；debugger visualizer；filtering；parameter estimation；voting algorithm