Minimal Solutions to Relative Pose Estimation From Two Views Sharing a Common Direction With Unknown Focal Length

Yaqing Ding, Jian Yang, Jean Ponce, Hui Kong

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

We propose minimal solutions to relative pose estimation problem from two views sharing a common direction with unknown focal length. This is relevant for cameras equipped with an IMU (inertial measurement unit), e.g., smart phones, tablets. Similar to the 6-point algorithm for two cameras with unknown but equal focal lengths and 7-point algorithm for two cameras with different and unknown focal lengths, we derive new 4- and 5-point algorithms for these two cases, respectively. The proposed algorithms can cope with coplanar points, which is a degenerate configuration for these 6- and 7-point counterparts. We present a detailed analysis and comparisons with the state of the art. Experimental results on both synthetic data and real images from a smart phone demonstrate the usefulness of the proposed algorithms.
Original languageEnglish
Title of host publicationIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)978-1-7281-7169-2
ISBN (Print)978-1-7281-7168-5
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020 - Virtual, Online, United States
Duration: 2020 Jun 142020 Jun 19

Conference

Conference2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020
Country/TerritoryUnited States
CityVirtual, Online
Period2020/06/142020/06/19

Subject classification (UKÄ)

  • Computer graphics and computer vision

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