The Resource Latency and distortion of electromagnetic trackers for augmented reality systems, Henry Himberg, Yuichi Motai, (electronic book)
Latency and distortion of electromagnetic trackers for augmented reality systems, Henry Himberg, Yuichi Motai, (electronic book)
Resource Information
The item Latency and distortion of electromagnetic trackers for augmented reality systems, Henry Himberg, Yuichi Motai, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Sydney Jones Library, University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item Latency and distortion of electromagnetic trackers for augmented reality systems, Henry Himberg, Yuichi Motai, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Sydney Jones Library, University of Liverpool.
This item is available to borrow from 1 library branch.
- Summary
- Augmented 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
- Language
- eng
- Extent
- 1 PDF (xv, 173 pages)
- Contents
-
- 1. Delta quaternion extended Kalman filter -- 1.1 Introduction -- 1.2 Related work -- 1.3 Background on orientation prediction -- 1.3.1 Extended Kalman filter -- 1.3.2 Quaternions -- 1.4 Filter design -- 1.4.1 Motion model -- 1.4.2 Quaternion framework -- 1.4.3 Delta quaternion framework -- 1.4.4 Quaternion prediction -- 1.4.5 Comparison of filter design -- 1.5 Experimental analysis -- 1.5.1 Experimental data -- 1.5.2 Tuning -- 1.5.3 Execution time -- 1.5.4 Prediction accuracy -- 1.5.5 Noise performance -- 1.6 Summary --
- 2. Multiple model delta quaternion filter -- 2.1 Introduction -- 2.2 Related work -- 2.3 Background -- 2.3.1 Quaternions and delta quaternion -- 2.3.2 Extended Kalman filter -- 2.3.3 Interacting multiple model estimator -- 2.4 Filter design -- 2.4.1 MMDQ design -- 2.4.2 Delta quaternion filter design -- 2.4.3 Orientation prediction -- 2.5 Experimental results -- 2.5.1 MMDQ configuration -- 2.5.2 TPM initialization -- 2.5.3 Measurement noise -- 2.5.4 Process noise -- 2.5.5 Angular velocity estimation -- 2.5.6 Prediction performance -- 2.5.7 Computational requirements -- 2.6 Summary --
- 3. Interpolation volume calibration -- 3.1 Introduction -- 3.2 Previous work -- 3.2.1 Managing the tracking volume -- 3.2.2 Single sensor compensation -- 3.2.3 Polynomial function methods -- 3.2.4 Look-up-table methods -- 3.2.5 Multiple sensor techniques -- 3.3 Background -- 3.3.1 Quaternions -- 3.3.2 AC magnetic tracking -- 3.4 Field mapping using IVC -- 3.4.1 Interpolation volume -- 3.4.2 Mapping fixture -- 3.4.3 Field data collection -- 3.4.4 Look-up-table (LUT) generation -- 3.5 Experimental results -- 3.5.1 PnO estimation using interpolation -- 3.5.2 Mapping fixture accuracy -- 3.5.3 Field data collection -- 3.5.4 Look-up-table (LUT) generation -- 3.6 Summary --
- 4. Conclusion -- A. The Delta Quaternion Extended Kalman Filter (DQEKF) -- B. Multiple Model Delta Quaternion Filter (MMDQ) -- C. Interpolation Volume Calibration (IVC) -- D. MatLab Library -- References -- Authors' biographies
- Isbn
- 9781627055086
- Label
- Latency and distortion of electromagnetic trackers for augmented reality systems
- Title
- Latency and distortion of electromagnetic trackers for augmented reality systems
- Statement of responsibility
- Henry Himberg, Yuichi Motai
- Subject
-
- calibration
- delta quaternion
- distributed body sensor
- extended Kalman filter
- head orientation
- head tracking
- human-computer interaction
- interacting multiple model estimator
- magnetic tracker
- motion tracking
- orientation
- position
- quaternion prediction
- real-time measurement
- AC magnetic tracking
- Augmented reality
- Tracking (Engineering)
- Language
- eng
- Summary
- Augmented 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
- Cataloging source
- CaBNVSL
- http://library.link/vocab/creatorName
- Himberg, Henry
- Dewey number
- 006.8
- Illustrations
- illustrations
- Index
- no index present
- LC call number
- QA76.9.A94
- LC item number
- H555 2014
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- abstracts summaries
- bibliography
- http://library.link/vocab/relatedWorkOrContributorName
- Motai, Yuichi.
- http://library.link/vocab/subjectName
-
- Augmented reality
- Tracking (Engineering)
- Target audience
-
- adult
- specialized
- Label
- Latency and distortion of electromagnetic trackers for augmented reality systems, Henry Himberg, Yuichi Motai, (electronic book)
- Bibliography note
- Includes bibliographical references (pages 163-171)
- Color
- multicolored
- Contents
-
- 1. Delta quaternion extended Kalman filter -- 1.1 Introduction -- 1.2 Related work -- 1.3 Background on orientation prediction -- 1.3.1 Extended Kalman filter -- 1.3.2 Quaternions -- 1.4 Filter design -- 1.4.1 Motion model -- 1.4.2 Quaternion framework -- 1.4.3 Delta quaternion framework -- 1.4.4 Quaternion prediction -- 1.4.5 Comparison of filter design -- 1.5 Experimental analysis -- 1.5.1 Experimental data -- 1.5.2 Tuning -- 1.5.3 Execution time -- 1.5.4 Prediction accuracy -- 1.5.5 Noise performance -- 1.6 Summary --
- 2. Multiple model delta quaternion filter -- 2.1 Introduction -- 2.2 Related work -- 2.3 Background -- 2.3.1 Quaternions and delta quaternion -- 2.3.2 Extended Kalman filter -- 2.3.3 Interacting multiple model estimator -- 2.4 Filter design -- 2.4.1 MMDQ design -- 2.4.2 Delta quaternion filter design -- 2.4.3 Orientation prediction -- 2.5 Experimental results -- 2.5.1 MMDQ configuration -- 2.5.2 TPM initialization -- 2.5.3 Measurement noise -- 2.5.4 Process noise -- 2.5.5 Angular velocity estimation -- 2.5.6 Prediction performance -- 2.5.7 Computational requirements -- 2.6 Summary --
- 3. Interpolation volume calibration -- 3.1 Introduction -- 3.2 Previous work -- 3.2.1 Managing the tracking volume -- 3.2.2 Single sensor compensation -- 3.2.3 Polynomial function methods -- 3.2.4 Look-up-table methods -- 3.2.5 Multiple sensor techniques -- 3.3 Background -- 3.3.1 Quaternions -- 3.3.2 AC magnetic tracking -- 3.4 Field mapping using IVC -- 3.4.1 Interpolation volume -- 3.4.2 Mapping fixture -- 3.4.3 Field data collection -- 3.4.4 Look-up-table (LUT) generation -- 3.5 Experimental results -- 3.5.1 PnO estimation using interpolation -- 3.5.2 Mapping fixture accuracy -- 3.5.3 Field data collection -- 3.5.4 Look-up-table (LUT) generation -- 3.6 Summary --
- 4. Conclusion -- A. The Delta Quaternion Extended Kalman Filter (DQEKF) -- B. Multiple Model Delta Quaternion Filter (MMDQ) -- C. Interpolation Volume Calibration (IVC) -- D. MatLab Library -- References -- Authors' biographies
- Control code
- 201404ASE012
- Dimensions
- unknown
- Extent
- 1 PDF (xv, 173 pages)
- File format
- multiple file formats
- Form of item
- online
- Isbn
- 9781627055086
- Other control number
- 10.2200/S00580ED1V01Y201404ASE012
- Other physical details
- illustrations.
- Reformatting quality
- access
- Specific material designation
- remote
- System details
- System requirements: Adobe Acrobat Reader
- Label
- Latency and distortion of electromagnetic trackers for augmented reality systems, Henry Himberg, Yuichi Motai, (electronic book)
- Bibliography note
- Includes bibliographical references (pages 163-171)
- Color
- multicolored
- Contents
-
- 1. Delta quaternion extended Kalman filter -- 1.1 Introduction -- 1.2 Related work -- 1.3 Background on orientation prediction -- 1.3.1 Extended Kalman filter -- 1.3.2 Quaternions -- 1.4 Filter design -- 1.4.1 Motion model -- 1.4.2 Quaternion framework -- 1.4.3 Delta quaternion framework -- 1.4.4 Quaternion prediction -- 1.4.5 Comparison of filter design -- 1.5 Experimental analysis -- 1.5.1 Experimental data -- 1.5.2 Tuning -- 1.5.3 Execution time -- 1.5.4 Prediction accuracy -- 1.5.5 Noise performance -- 1.6 Summary --
- 2. Multiple model delta quaternion filter -- 2.1 Introduction -- 2.2 Related work -- 2.3 Background -- 2.3.1 Quaternions and delta quaternion -- 2.3.2 Extended Kalman filter -- 2.3.3 Interacting multiple model estimator -- 2.4 Filter design -- 2.4.1 MMDQ design -- 2.4.2 Delta quaternion filter design -- 2.4.3 Orientation prediction -- 2.5 Experimental results -- 2.5.1 MMDQ configuration -- 2.5.2 TPM initialization -- 2.5.3 Measurement noise -- 2.5.4 Process noise -- 2.5.5 Angular velocity estimation -- 2.5.6 Prediction performance -- 2.5.7 Computational requirements -- 2.6 Summary --
- 3. Interpolation volume calibration -- 3.1 Introduction -- 3.2 Previous work -- 3.2.1 Managing the tracking volume -- 3.2.2 Single sensor compensation -- 3.2.3 Polynomial function methods -- 3.2.4 Look-up-table methods -- 3.2.5 Multiple sensor techniques -- 3.3 Background -- 3.3.1 Quaternions -- 3.3.2 AC magnetic tracking -- 3.4 Field mapping using IVC -- 3.4.1 Interpolation volume -- 3.4.2 Mapping fixture -- 3.4.3 Field data collection -- 3.4.4 Look-up-table (LUT) generation -- 3.5 Experimental results -- 3.5.1 PnO estimation using interpolation -- 3.5.2 Mapping fixture accuracy -- 3.5.3 Field data collection -- 3.5.4 Look-up-table (LUT) generation -- 3.6 Summary --
- 4. Conclusion -- A. The Delta Quaternion Extended Kalman Filter (DQEKF) -- B. Multiple Model Delta Quaternion Filter (MMDQ) -- C. Interpolation Volume Calibration (IVC) -- D. MatLab Library -- References -- Authors' biographies
- Control code
- 201404ASE012
- Dimensions
- unknown
- Extent
- 1 PDF (xv, 173 pages)
- File format
- multiple file formats
- Form of item
- online
- Isbn
- 9781627055086
- Other control number
- 10.2200/S00580ED1V01Y201404ASE012
- Other physical details
- illustrations.
- Reformatting quality
- access
- Specific material designation
- remote
- System details
- System requirements: Adobe Acrobat Reader
Subject
- calibration
- delta quaternion
- distributed body sensor
- extended Kalman filter
- head orientation
- head tracking
- human-computer interaction
- interacting multiple model estimator
- magnetic tracker
- motion tracking
- orientation
- position
- quaternion prediction
- real-time measurement
- AC magnetic tracking
- Augmented reality
- Tracking (Engineering)
Member of
- Online access with purchase: Morgan & Claypool (Synthesis Collection Five)
- Synthesis digital library of engineering and computer science
- Synthesis lectures on algorithms and software in engineering, # 12.
- Synthesis lectures on algorithms and software in engineering, 12
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Latency-and-distortion-of-electromagnetic/4oMynaYD7Jw/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Latency-and-distortion-of-electromagnetic/4oMynaYD7Jw/">Latency and distortion of electromagnetic trackers for augmented reality systems, Henry Himberg, Yuichi Motai, (electronic book)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">Sydney Jones Library, University of Liverpool</a></span></span></span></span></div>
