Abstract
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.
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Acknowledgements
Partial funding for this study was provided by NSF PACI REU program.
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Kindratenko, V.V., Sherman, W.R. Neural network-based calibration of electromagnetic tracking systems. Virtual Reality 9, 70–78 (2005). https://doi.org/10.1007/s10055-005-0005-3
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DOI: https://doi.org/10.1007/s10055-005-0005-3