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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bleser, G. Stricker, D. |
| Copyright Year | 2008 |
| Description | Author affiliation: Tech. Univ. Darmstadt, Darmstadt (Bleser, G.; Stricker, D.) |
| Abstract | We present a new visual-inertial tracking device for augmented and virtual reality applications. The paper addresses two fundamental issues of such systems. The first one concerns the definition and modelling of the sensor fusion. Much work has been done in this area and several models for exploiting the data of the gyroscopes and linear accelerometers have been proposed. However, the respective advantages of each model and in particular the benefits of the integration of the accelerometer data in the filter are still unclear. The paper therefore provides an evaluation of different models with special investigation of the effects of using accelerometers on the tracking performance. The second contribution is about the development of an image processing approach that does not require special landmarks but uses natural features. Our solution relies on a 3D model of the scene that enables to predict the appearances of the features by rendering the model using the prediction data of the sensor fusion filter. The feature localisation is robust and accurate mainly because local lighting is also estimated. The final system is evaluated with help of ground-truth and real data. High stability and accuracy is demonstrated also for large environments. |
| Starting Page | 137 |
| Ending Page | 144 |
| File Size | 7429475 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424419715 |
| DOI | 10.1109/VR.2008.4480765 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-03-08 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image processing Sensor fusion Accelerometers Filters Predictive models Virtual reality Gyroscopes Layout Rendering (computer graphics) Robustness Verification augmented reality markerless camera tracking model-based tracking inertial sensors sensor fusion extended 1.4.8 [Image processing and computer vision]: Scene analysis-Motion, Photometry, Sensor fusion, Tracking I.2.10 [Artificial intelligence]: Vision and Scene Understanding 3D/stereo scene analysis, Intensity, color, photometry, and thresholding, Motion, Texture, Video analysis I.5.5 [Pattern recognition]: Applications¿Computer vision G. 3 [Probability and statistics]: Markov processes, Probabilistic algorithms, Robust regression, Stochastic processes I.2.9 [Artificial intelligence]: Robotics¿ Kinematics and dynamics, Sensors I.3.m [Computer graphics]: Miscellaneous¿Augmented Reality Algorithms Experimentation Performance Theory |
| Content Type | Text |
| Resource Type | Article |
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