Abstract
Augmented Reality (AR) tries to seamlessly integrate virtual content into the real world of the user. Ideally, the virtual content would behave exactly like real objects. This requires a correct and precise estimation of the user’s viewpoint (respectively that of a camera) with respect to the coordinate system of the virtual content. This can be achieved by an appropriate 6-DoF tracking system.
In this chapter we will present a general approach for a computer vision (CV) based tracking system applying an adaptive feature based tracker. We will present in detail the individual steps of the tracking pipeline and discuss a sample implementation based on SURF feature descriptors, allowing for easy understanding of the individual steps necessary upon building your own CV tracker.
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References
H. Bay, A. Ess, T. Tuytelaars, and L. van Gool, “Speeded-up robust Features (SURF),” Computer Vision and Image Understanding (CVIU), Volume 110, No. 3, pages 346–359, 2008
D. C. Brown, “Close-range camera calibration,” Photogrammetric Engineering, Volume 37, Number 8, pages 855–866, 1971
D. Cheng, S. Xie, and E. Hämmerle, “Comparison of local descriptors for image registration of geometrically-complex 3D scenes,” 14th International Conference on Mechatronics and Machine Vision in Patrice (M2VIP), pages 140–145, 2007
A. J. Davison, and N. Kita, “3D simultaneous localisation and map-building using active vision for a robot moving on undulating terrain,” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Kauai, 2001
M. A. Fischler, and R. C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Communications of the ACM 24, Volume 6, 1981
C. Harris, and M. Stephens, “A Combined Corner and Edge Detector,” Proceedings of the 4th Alvey Vision Conference, pages 147–151, 1988
J. Herling and W. Broll, “An Adaptive Training Free Tracker for Mobile Phones”, In Proc. of the 17th ACM Conference on Virtual Reality Systems and Technology (VRST 2010), ACM, New York, NY, USA, pages 35–42
H. Kato, and M. Billinghurst, “Marker Tracking and HMD Calibration for a Video-based Augmented Reality Conferencing System”, in2nd IEEE and ACM International Workshop on Augmented Reality, 1999
G. Klein, and D. Murray, “Parallel Tracking and Mapping for Small AR Workspaces”, Proc. of IEEE ISMAR, 2007
G. Klein, and D. Murray, “Parallel Tracking and Mapping on a Camera Phone”, Proc. of IEEE ISMAR, 2009
V. Lepetit, P. Lagger, and P. Fua, “Randomized Trees for Real-Time Keypoint Recognition,” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pages 775–781, 2005
V. Lepetit, F. Moreno-Noguer, and P. Fua, “EPnP: An Accurate O(n) Solution to the PnP Problem,” International Journal of Computer Vision, Volume 81, Issue 2, 2009
D. G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints,” International Journal of Computer Vision. Volume 60 Issue 2, 2004
W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B.P. Flannery, “Numerical Recipes: The Art of Scientific Computing,” Cambridge University Press, Third Edition, 2007
M. Özuysal, P. Fua, and V. Lepetit, “Fast Keypoint Recognition in Ten Lines of Code,” Proceedings of IEEE Conference on Computing Vision and Pattern Recognition, pages 1–8, 2007
E. Rosten, and T. Drummond, “Fusing Points and Lines for High Performance Tracking,” Proceedings of the IEEE International Conference on Computer Vision, pages 1508–1511, 2005
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© 2011 Springer Science+Business Media, LLC
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Herling, J., Broll, W. (2011). Markerless Tracking for Augmented Reality. In: Furht, B. (eds) Handbook of Augmented Reality. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0064-6_11
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DOI: https://doi.org/10.1007/978-1-4614-0064-6_11
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