测绘通报 ›› 2021, Vol. 0 ›› Issue (7): 135-139.doi: 10.13474/j.cnki.11-2246.2021.0224

• 技术交流 • 上一篇    下一篇

利用基本矩阵重构地面影像位姿信息

张庆斌1, 赵之星1, 鲁小红2, 薛永安3   

  1. 1. 中晋环境科技有限公司, 山西 太原 030002;
    2. 山西省矿山调查测量队, 山西 太原 030024;
    3. 太原理工大学矿业工程学院, 山西 太原 030024
  • 收稿日期:2021-04-26 修回日期:2021-05-25 出版日期:2021-07-25 发布日期:2021-08-04
  • 作者简介:张庆斌(1980-),男,硕士,高级工程师,主要从事无人机摄影测量、近景摄影测量、大数据信息平台等研究。E-mail:zjhjzqb@163.com

Reconstruct the position and orientation of the complementary image by basic matrix

ZHANG Qingbin1, ZHAO Zhixing1, LU Xiaohong2, XUE Yongan3   

  1. 1. Zhongjin Environment Technology Co., Ltd., Taiyuan 030002, China;
    2. Shanxi Mining Survey Team, Taiyuan 030024, China;
    3. College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China
  • Received:2021-04-26 Revised:2021-05-25 Online:2021-07-25 Published:2021-08-04

摘要: 在地面采集的盲区影像往往缺少位姿信息,进而与空中影像联合处理时造成分层错乱。因此为提高倾斜模型精细度,本文通过约束对极奇异矩阵的方法重构补拍影像的位置姿态。首先进行空地影像特征匹配,得出两者的基本矩阵,规范化空中影像投影矩阵,地面影像投影矩阵则由基本矩阵分解成的反对称矩阵和非奇异矩阵组成;然后利用空中影像POS信息消除该投影矩阵对的多义性,从而得出地面影像位置姿态的准确值。试验结果表明,该方法能够在无像控条件下自动计算出地面盲区补拍影像的位姿信息且与空中影像配准良好,在保证模型精细的前提下提高了作业效率。

关键词: 精细化模型, 位姿信息, 基本矩阵, 多义性, 无像控条件

Abstract: The blind spot images collected on the ground often lack pose information, which will cause stratification when combined with aerial image processing. Therefore, to improve the precision of the tilt model a new method is proposed to reconstruct the position and attitude of the complementary image by constraining the pair extreme singular matrix. Firstly, feature matching is carried out to obtain the pair singular matrix, namely the fundamental matrix. The projection matrix of aerial image is assumed to be normalized, and the projection matrix of ground image is composed of anti-symmetric matrix and non-singular matrix decomposed from the basic matrix. Then, the POS information of aerial image is used to eliminate the ambiguity of the projection matrix pair, so as to obtain the accurate position and posture value of the ground image. The test results show that this method can automatically calculate the position and pose information of the ground blind area retaking image without image control, and it is well matched with the aerial image, which improves the operation efficiency under the premise of ensuring the precision of the model.

Key words: fine modeling, position and orientation, fundamental matrix, ambiguity, image-free control

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