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兵工学报 ›› 2012, Vol. 33 ›› Issue (8): 902-911.doi: 10.3969/j.issn.1000-1093.2012.08.002

• 论文 • 上一篇    下一篇

一种由粗及精的视线追踪系统平面视线参数检测方法

迟健男1, 张闯1, 陈凯2, 胡涛1   

  1. (1.北京科技大学 钢铁流程先进控制教育部重点实验室, 北京 100083;2.北京控制工程研究所, 北京 100190)
  • 收稿日期:2011-01-10 修回日期:2011-01-10 上线日期:2014-03-04
  • 作者简介:迟健男(1967—),男,副教授
  • 基金资助:
    北京市重点学科建设项目(XK100080537);北京市自然科学基金项目(4122050)

Planar Gaze Parameter Detection in Gaze Tracking System with Active Infrared Light Source

CHI Jian-nan1, ZHANG Chuang1, CHEN Kai2, HU Tao1   

  1. (1.Ministry of Education, Key Laboratory for Advanced Control of Iron and Steel Process, University of Scienceand Technology Beijing, Beijing 100083, China;2.Beijing Institute of Control Engineering, Beijing 100190, China)
  • Received:2011-01-10 Revised:2011-01-10 Online:2014-03-04

摘要: 针对视线追踪系统视线参数检测需求和现有方法的不足,基于亮暗瞳差分方案提出了一种采用由粗及精策略的平面视线参数检测方法。在暗瞳图像应用AdaBoost方法定位人脸,根据人脸五官分布先验知识初步确定人眼区域并标记暗瞳图像对应的人眼区域。在差分图像采用投影法确定瞳孔潜在区域,通过形态和尺度分析滤波定位瞳孔。对瞳孔进行边缘检测和椭圆拟合,提取瞳孔中心参数。在暗瞳图像瞳孔对应区域附近搜索并检测普尔钦斑并提取普尔钦斑中心参数。根据瞳孔和普尔钦斑中心参数获取平面视线参数。在视线追踪系统中的应用表明该方法能够可靠、精确的检测平面视线参数。

关键词: 〖JP2〗信息处理技术, 视线追踪, 平面视线参数, 亮瞳图像, AdaBoost, 瞳孔检测, 椭圆拟合〖JP〗

Abstract: In order to meet the requirements and improve the existing methods for parameter detection in gaze tracking system, an approach based on difference image of bright and dark pupils for planar gaze parameter detection was proposed. First, an iteration algorithm called AdaBoost was used to find human face, and according to the priori knowledge of facial features, the eye region was determined and marked in the dark pupil image preliminarily. Then, in difference image, a projection method was applied to locate the possible area of pupil, and pupil would be detected accurately by analyzing its shape and scale. Furthermore, edge detection and an ellipse fitting were used to extract the pupil center parameters, and in the corresponding pupil region in dark pupil image, Purkinje spot and its center parameters were detected. The planar gaze parameters were then calculated according to the center parameters of pupil and Purkinje spot. Applications in gaze tracking system show that the method can detect the planar sight parameters accurately.

Key words: information processing, gaze tracking, planar parameter of sight, bright pupil image, AdaBoost, pupil detection, ellipse fitting

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