计算机与现代化 ›› 2020, Vol. 0 ›› Issue (10): 97-102.

• 模式识别 • 上一篇    下一篇

增强现实与视觉惯导模块的位姿融合方法

  

  1. (华北计算技术研究所,北京100083)
  • 出版日期:2020-10-14 发布日期:2020-10-14
  • 作者简介:聂雷航(1995—),男,湖北宜昌人,硕士研究生,研究方向:增强现实,同时定位与地图构建,E-mail: 305175355@qq.com; 聂芸(1973—),女,山东济宁人,高级工程师,硕士,研究方向:虚拟现实,增强现实,图形图像处理,E-mail: nie1973cn@aliyun.com; 王国伟(1990—),男,山东日照人,工程师,硕士,研究方向:计算机视觉,计算机体系结构,E-mail: 3386935301@qq.com。

A Pose Fusion Method of Augmented Reality and Visual Inertial Navigation Module

  1. (North China Institute of Computing Technology, Beijing 100083, China)
  • Online:2020-10-14 Published:2020-10-14

摘要: 基于视觉标志物的增强现实技术和视觉惯性里程计(VIO)技术有着良好的互补性。本文针对当前基于视觉标志物的增强现实系统依赖标志物以及VIO的缺乏地理位置信息、累计误差等问题,提出一种泛用的位姿融合方法,该方法可以将任意的2种不同坐标系下的相同轨迹位姿输出转换到同一坐标系下。针对本文的问题,实现基于视觉标志物的增强现实与视觉惯导模块的位姿融合,并利用视觉标志物自身带有地理信息的特点,为整个系统提供真实的地理信息坐标,使得定位系统能够与地理信息系统相结合。以实时通讯的方式采集华为P10手机输出的图像与IMU信息作为数据源,在Ubuntu16.04和Unity游戏引擎上进行实验。结果表明,本文方法能够有效地完成准确的位姿融合。

关键词: 增强现实, 视觉标志物, 视觉惯性里程计, 地理信息, 位姿融合

Abstract: Augmented reality technology based on visual markers and visual inertia odometer (VIO) technology have good complementarity. In this paper, a general pose fusion method is proposed to solve the problems of the current augmented reality system based on markers and VIO’s lack of geographic location information and cumulative errors. This method can transform the output of the same trajectory pose in arbitrary two different coordinate systems to the same coordinate system. Aiming at the problems in this paper, we realize the integration of the position and pose of the augmented reality based on visual markers and the visual inertial navigation module, and provide the real geographic information coordinates for the whole system by using the characteristics of the geographic information of the visual markers, so that the positioning system can be combined with the geographic information system. The image and IMU information output from Huawei P10 phone are collected in the form of real-time communication as the data source, and experiment is conducted on Ubuntu16.04 and Unity game engine. The results show that the proposed method can achieve accurate pose fusion effectively.

Key words: augmented reality, visual markers, visual inertia odometer, geographic information, pose fusion