000 03863nam a22004935i 4500
001 978-3-031-01522-9
003 DE-He213
005 20240730164327.0
007 cr nn 008mamaa
008 220601s2014 sz | s |||| 0|eng d
020 _a9783031015229
_9978-3-031-01522-9
024 7 _a10.1007/978-3-031-01522-9
_2doi
050 4 _aTK5102.9
072 7 _aTJF
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC067000
_2bisacsh
072 7 _aTJF
_2thema
072 7 _aUYS
_2thema
082 0 4 _a621,382
_223
100 1 _aHimberg, Henry.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983928
245 1 0 _aLatency and Distortion of Electromagnetic Trackers for Augmented Reality Systems
_h[electronic resource] /
_cby Henry Himberg, Yuichi Motai.
250 _a1st ed. 2014.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXV, 173 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Algorithms and Software in Engineering,
_x1938-1735
505 0 _aList of Tables -- Preface -- Acknowledgments -- Delta Quaternion Extended Kalman Filter -- Multiple Model Delta Quaternion Filter -- Interpolation Volume Calibration -- Conclusion -- References -- Authors' Biographies .
520 _aAugmented reality (AR) systems are often used to superimpose virtual objects or information on a scene to improve situational awareness. Delays in the display system or inaccurate registration of objects destroy the sense of immersion a user experiences when using AR systems. AC electromagnetic trackers are ideal for these applications when combined with head orientation prediction to compensate for display system delays. Unfortunately, these trackers do not perform well in environments that contain conductive or ferrous materials due to magnetic field distortion without expensive calibration techniques. In our work we focus on both the prediction and distortion compensation aspects of this application, developing a "small footprint" predictive filter for display lag compensation and a simplified calibration system for AC magnetic trackers. In the first phase of our study we presented a novel method of tracking angular head velocity from quaternion orientation using an Extended KalmanFilter in both single model (DQEKF) and multiple model (MMDQ) implementations. In the second phase of our work we have developed a new method of mapping the magnetic field generated by the tracker without high precision measurement equipment. This method uses simple fixtures with multiple sensors in a rigid geometry to collect magnetic field data in the tracking volume. We have developed a new algorithm to process the collected data and generate a map of the magnetic field distortion that can be used to compensate distorted measurement data. Table of Contents: List of Tables / Preface / Acknowledgments / Delta Quaternion Extended Kalman Filter / Multiple Model Delta Quaternion Filter / Interpolation Volume Calibration / Conclusion / References / Authors' Biographies.
650 0 _aSignal processing.
_94052
650 1 4 _aSignal, Speech and Image Processing.
_931566
700 1 _aMotai, Yuichi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983929
710 2 _aSpringerLink (Online service)
_983932
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031003943
776 0 8 _iPrinted edition:
_z9783031026508
830 0 _aSynthesis Lectures on Algorithms and Software in Engineering,
_x1938-1735
_983933
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01522-9
912 _aZDB-2-SXSC
942 _cEBK
999 _c85585
_d85585