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A Minimal Closed-Form Solution for Multi-perspective Pose Estimation using Points and Lines

  • Pedro Miraldo
  • Tiago Dias
  • Srikumar Ramalingam
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11220)

Abstract

We propose a minimal solution for pose estimation using both points and lines for a multi-perspective camera. In this paper, we treat the multi-perspective camera as a collection of rigidly attached perspective cameras. These type of imaging devices are useful for several computer vision applications that require a large coverage such as surveillance, self-driving cars, and motion-capture studios. While prior methods have considered the cases using solely points or lines, the hybrid case involving both points and lines has not been solved for multi-perspective cameras. We present the solutions for two cases. In the first case, we are given 2D to 3D correspondences for two points and one line. In the later case, we are given 2D to 3D correspondences for one point and two lines. We show that the solution for the case of two points and one line can be formulated as a fourth degree equation. This is interesting because we can get a closed-form solution and thereby achieve high computational efficiency. The later case involving two lines and one point can be mapped to an eighth degree equation. We show simulations and real experiments to demonstrate the advantages and benefits over existing methods.

Keywords

Multi-perspective camera Pose estimation Points Lines 

Notes

Acknowledgments

P. Miraldo and T. Dias are with the Institute for Systems and Robotics (ISR/IST), LARSyS, Instituto Superior Técnico, University of Lisboa, Portugal. This work was partially supported by the Portuguese projects [UID/EEA/50009/2013] & [PTDC/EEI-SII/4698/2014] and grant [SFRH/BPD/111495/2015]. We thank the reviewers and ACs for valuable feedback.

Supplementary material

474218_1_En_29_MOESM1_ESM.pdf (172 kb)
Supplementary material 1 (pdf 171 KB)

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Instituto Superior TécnicoLisboaPortugal
  2. 2.School of ComputingUniversity of UtahSalt Lake CityUSA

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