黄碧辉, 吴勇, 郑森源, 林月煌. 一种改进的户外移动增强现实三维注册方法[J]. 武汉大学学报 ( 信息科学版), 2019, 44(12): 1865-1873. doi: 10.13203/j.whugis20180098
引用本文: 黄碧辉, 吴勇, 郑森源, 林月煌. 一种改进的户外移动增强现实三维注册方法[J]. 武汉大学学报 ( 信息科学版), 2019, 44(12): 1865-1873. doi: 10.13203/j.whugis20180098
HUANG Bihui, WU Yong, ZHENG Senyuan, LIN Yuehuang. An Improved Registration Method for Outdoor Mobile Augmented Reality[J]. Geomatics and Information Science of Wuhan University, 2019, 44(12): 1865-1873. doi: 10.13203/j.whugis20180098
Citation: HUANG Bihui, WU Yong, ZHENG Senyuan, LIN Yuehuang. An Improved Registration Method for Outdoor Mobile Augmented Reality[J]. Geomatics and Information Science of Wuhan University, 2019, 44(12): 1865-1873. doi: 10.13203/j.whugis20180098

一种改进的户外移动增强现实三维注册方法

An Improved Registration Method for Outdoor Mobile Augmented Reality

  • 摘要: 针对目前移动增强现实三维注册实时性不强和鲁棒性差的问题,提出一种基于改进加速鲁棒性特征(speed up robust features,SURF)算法和角点跟踪算法(Kanade-Lucas-Tomasi,KLT)的移动增强现实户外三维注册方法。该方法通过结合快速视网膜关键点(fast retina keypoint,FREAK)算法改进了SURF算法(简称SUFREAK),提高算法描述子构建效率,并保持了算法的鲁棒性。利用视频帧间的相关性,采用KLT光流跟踪算法对户外场景的自然特征点进行跟踪预测,以提高三维注册的实时性。实验结果表明,在户外复杂环境条件下,改进SURF算法具有较高的实时性和鲁棒性,且基于改进SURF和KLT算法的移动增强现实三维注册具有良好的实时性和图像识别效率。

     

    Abstract: Aiming at the poor real-time and robustness of registration method for outdoor augmented reality while mobile devices was used, a new image registration method based on improved speed up robust features (SURF) algorithm and Kanade-Lucas-Tomasi (KLT) algorithm in the mobile augmented reality is proposed. The method improves the SURF algorithm by combining the fast retina keypoint (FREAK) algorithm which has a very good performance of extracting descriptors, expressed in speed, quality and quantity, SUFREAK algorithm is formed. It makes up for the shortcoming of slow feature points extraction in SURF algorithm. SUFREAK algorithm improves the descriptor extraction efficiency and maintains the better robustness of the algorithm at the same time. Using the correlation between the close frames of video, the KLT optical flow tracking algorithm is used to track and predict the position of natural feature points in the open air, it will be effective to improving the real-time performance of image registration method. The experimental results show that the improved SURF algorithm has higher real-time performance and robustness under complex outdoor environment conditions, and the registration method of mobile augmented reality based on improved SURF and KLT algorithm has a good real-time performance of system and the efficiency of image recognition has been greatly improved.

     

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