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003			ES-MaUEC
005			20230124105631.0
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007			cr nn 008mamaa
008			220601s2014 sz | o |||| 0|eng d
020			_a9783031015229
024	7		_a10.1007/978-3-031-01522-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.A94 _b2014 EB
100	1		_aHimberg, Henry _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686136
245	1	0	_aLatency and Distortion of Electromagnetic Trackers for Augmented Reality Systems _cby Henry Himberg, Yuichi Motai
250			_a1st edition 2014
264		1	_aCham _bSpringer International Publishing _c2014
300			_a1 recurso en línea (XV, 173 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_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 Kalman Filter 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.
988			_aSynthesis Collection of Technology_2014
650		7	_2embne _9679169 _aRealidad aumentada
650		7	_2embne _9146720 _aEstimación estadística
700	1		_aMotai, Yuichi _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686137
776	0	8	_iPrinted edition: _z9783031003943
776	0	8	_iPrinted edition: _z9783031026508
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01522-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _eb _zSI