Neural network-based calibration of electromagnetic tracking systems

Volodymyr Kindratenko, William R. Sherman

Research output: Contribution to journalArticlepeer-review


Electromagnetic tracking systems are a common component of many virtual reality installations. Their accuracy, however, suffers from the distortions of the electromagnetic field used in calculating the tracker sensor's position. We have developed a tracker calibration technique based on a neural network that effectively compensates for the errors in both tracked location and orientation. This case study discusses our implementation of the calibration algorithm and compares the results with traditional calibration methods.

Original languageEnglish (US)
Pages (from-to)70-78
Number of pages9
JournalVirtual Reality
Issue number1
StatePublished - Dec 1 2005


  • Electromagnetic tracker
  • Neural network
  • Tracker calibration
  • Virtual reality

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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