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兵工学报 ›› 2018, Vol. 39 ›› Issue (5): 1006-1011.doi: 10.3969/j.issn.1000-1093.2018.05.022

• 论文 • 上一篇    下一篇

光学透射式汽车抬头显示器系统的虚实注册方法研究

安喆, 徐熙平, 杨进华, 乔杨, 吕耀文, 刘洋   

  1. (长春理工大学 光电工程学院, 吉林 长春 130022)
  • 收稿日期:2017-08-25 修回日期:2017-08-25 上线日期:2018-06-22
  • 作者简介:安喆(1992—),女,博士研究生。E-mail: 2955100200@qq.com
  • 基金资助:
    国家自然科学基金项目(61605016);吉林省重点科技攻关项目(20160204062GX)

Research on Virtual Reality Registration Method for Optical See-through HUD System

AN Zhe, XU Xi-ping, YANG Jin-hua, QIAO Yang, LYU Yao-wen, LIU Yang   

  1. (School of Opto-Electronic Engineering, Changchun University of Science and Technology, Changchun 130022, Jilin, China)
  • Received:2017-08-25 Revised:2017-08-25 Online:2018-06-22

摘要: 针对光学透射式汽车抬头显示器(HUD)增强现实系统的虚实注册问题,提出一种无标识虚实注册方法。介绍了HUD系统组成,并对系统各部分进行坐标定义;建立了各坐标系转换关系,得到初始注册矩阵。随后获取图像对,对图像进行特征提取,利用最小化灰度测量误差方法建立图像间的关系。采用非线性优化方法求解公式,对相机姿态进行估计,得到当前状态下的注册矩阵。通过合成初始矩阵与当前矩阵得到HUD系统的虚实注册矩阵。实验结果表明,系统的注册值与真实值相关距离为0.088 9,满足注册精度要求,且对比于其他方法,算法速度有所提高。

关键词: 光学透射式汽车抬头显示器, 虚实注册, 灰度测量误差, 非线性优化

Abstract: A method for registrating the virtual reality without identification is presented for virtual reality registration of optical see-through automotive head-up display (HUD) in augmented reality system. The composition of HUD system is introduced, the coordinates of each part of the system are defined, and the transformation relations of each coordinate system are established. The initial registration matrix is obtained. Then the image pairs are got to extract the features of image, and the relationship between the images is established by using the method of gray measuring error. Finally, the virtual reality registration matrix of HUD system is obtained by synthesizing the initial matrix and the current matrix. The experimental results show that the correlation distance between the registered value and the real value of the system is 0.088 9, which meets the requirement of registration accuracy. Compared to other methods, the algorithm speed has been improved.Key

Key words: opticalsee-throughhead-updisplay, virtualrealityregistration, measuringerrorofgraylevel, nonlinearoptimization

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