Calibration, Positioning and Tracking in a Refractive and Reflective Scene

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

We propose a framework for calibration, positioning
and tracking in a scene viewed by multiple cameras, through
a flat refractive surface and one or several flat reflective walls.
Refractions are explicitly modeled by Snell’s law and reflections
are handled using virtual points. A novel bundle adjustment
framework is introduced for solving the nonlinear equations
of refractions and the linear equations of reflections, which in
addition enables optimization for calibration and positioning. The
numerical accuracy of the solutions is investigated on synthetic
data, and the influence of noise in image points for several settings
of refractive and reflective planes is presented. The performance of
the framework is evaluated on real data and confirms the validity
of the physical model. Examples of how to use the framework
to back-project image coordinates, forward-project scene points
and estimate the refractive and reflective planes are presented.
Lastly, an application of the system on real data from a biological
experiment on small aquatic organisms is presented.

Details

Authors
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Mathematics
  • Computer Vision and Robotics (Autonomous Systems)
Original languageEnglish
Title of host publication Pattern Recognition (ICPR), 2016 23rd International Conference on
PublisherIEEE--Institute of Electrical and Electronics Engineers Inc.
Pages3810-3815
Number of pages6
ISBN (Electronic)978-1-5090-4847-2
Publication statusPublished - 2017 Apr 24
Publication categoryResearch
Peer-reviewedYes
Event2016 23rd International Conference on Pattern Recognition (ICPR 2016) - Cancún Center, Cancún, Mexico
Duration: 2016 Dec 42016 Dec 8
http://www.icpr2016.org/site/

Conference

Conference2016 23rd International Conference on Pattern Recognition (ICPR 2016)
Abbreviated titleICPR 2016
CountryMexico
CityCancún
Period2016/12/042016/12/08
Internet address

Related research output

Palmér, T., 2017 Feb 9, 1 ed. Lund: Faculty of Engineering, Centre for Mathematical Sciences, Mathematical Statistics, Lund University. 299 p.

Research output: ThesisDoctoral Thesis (compilation)

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