Acta Optica Sinica, Volume. 41, Issue 5, 0515001(2021)

Decoupling Relative Pose Estimation Method for Non-Overlapping Multi-Camera System

Miao Tian1,2, Banglei Guan1,2、*, Fang Sun3, Yun Yuan4, and Qifeng Yu1,2
Author Affiliations
  • 1College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, Hunan 410073, China
  • 2Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation, National University of Defense Technology, Changsha, Hunan 410073, China
  • 3Army Aviation Institute, Beijing 101123, China
  • 4Rocket Force Academy, Beijing 100089, China
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    In autonomous driving applications, the vision-based relative pose estimation is one of the core technologies to realize self-positioning of driverless cars. Aiming at the problems that the monocular vision system has a small field of view and the binocular vision system needs a overlapping field of view, a method for decoupling relative pose estimation of multi-camera systems with non-overlapping field of view is proposed. Use the different characteristics of the near and far points in the scene to decouple the rotation matrix and the translation vector. The relative rotation matrix is solved by the histogram voting method for the feature points of the distant scene, and the relative translation is solved by the sampling height method for the feature points of the near scene under the condition that the relative rotation matrix is known. The feasibility, robustness and accuracy of the proposed method are verified through simulation and actual experiment. Experimental results show that the relative attitude accuracy of the proposed method is better than 0.05°, and the relative translation vector direction accuracy is better than 2.5°, which has higher accuracy and better robustness.

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    Miao Tian, Banglei Guan, Fang Sun, Yun Yuan, Qifeng Yu. Decoupling Relative Pose Estimation Method for Non-Overlapping Multi-Camera System[J]. Acta Optica Sinica, 2021, 41(5): 0515001

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    Paper Information

    Category: Machine Vision

    Received: Sep. 27, 2020

    Accepted: Nov. 2, 2020

    Published Online: Apr. 7, 2021

    The Author Email: Guan Banglei (guanbanglei12@nudt.edu.cn)

    DOI:10.3788/AOS202141.0515001

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