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Increasing the Tracking Efficiency of Mobile Augmented Reality Using a Hybrid Tracking Technique

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Advances in Visual Informatics (IVIC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8237))

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Abstract

Traditional vision tracking approaches have failed to support the fast tracking required by Mobile Augmented Reality (MAR) for a real-time interactive effect. The main problem addressed by this research is the tracking problem in MAR where the computational load is a major issue. In this paper we proposed a more efficient visual tracking technique based on fast detectors and small binary descriptors which are capable of providing both; scale and rotation invariance. We also propose a new hybrid tracking technique which can speed up the overall performance of MAR by reducing the detection rate of the tracking process. The hybrid technique is based on the usage of inertial sensors such as accelerometer, gyroscopes and gravitational vectors which can readily improve the efficiency of any vision based feature tracking system that uses computer vision. The preliminary tests carried out during the course of the study produced very promising results.

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References

  1. Bai, H., Lee, G.: Interaction Methods for Mobile Augmented Reality. In: Proceedings of the 13th International Conference of the NZ Chapter of the ACM’s Special Interest Group on Human-Computer Interaction (CHINZ 2012), p. 101 (2012)

    Google Scholar 

  2. Wagner, D., Schmalstieg, D.: ARToolKitPlus for Pose Tracking on Mobile Devices. In: Computer Vision Winter Workshop, pp. 1-8 (2007)

    Google Scholar 

  3. Wagner, D., Reitmayr, G., Mulloni, A., Drummond, T., Schmalstieg, D.: Pose tracking from natural features on mobile phones. In: Int. Symp. on Mixed and Augmented Reality, pp. 125–134 (2008)

    Google Scholar 

  4. Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. Journal of Computer Vision 60(2), 91–110 (2004)

    Google Scholar 

  5. Rosten, E., Drummond, T.: Fusing Points and Lines for High Performance Tracking. In: Proceedings of the Tenth IEEE International Conference on Computer Vision, vol. 2 (2005)

    Google Scholar 

  6. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features. Computer Vision and Image Understanding 110(3), 346–359 (2008)

    Article  Google Scholar 

  7. Calonder, M., Lepetit, V., Strecha, C., Fua, P.: BRIEF: Binary robust independent elementary features. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 778–792. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  8. Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: Orb: an efficient alternative to sift or surf (2011)

    Google Scholar 

  9. Leutenegger, S., Chli, M., Siegwart, R.: Brisk: Binary robust invariant scalable keypoints (2011)

    Google Scholar 

  10. Alahi, A., Ortiz, R., Vandergheynst, P.: FREAK: Fast Retina Keypoint. In: IEEE Conference on Computer Vision and Pattern Recognition (2012)

    Google Scholar 

  11. Vallino, J.R.: Interactive Augmented Reality. Thesis Doctor of Philosophy, Department of Computer Science, University of Rochester (1998)

    Google Scholar 

  12. Sutherland, I.E.: The Ultimate Display. In: Proceedings of the IFIP Congress, New York, vol. 2, pp. 506–508 (1965)

    Google Scholar 

  13. Rosenblum, L., Julier, S.: Projects in VR, Making Augmented Reality Practical on Mobile Phones, Part 1, pp. 1–4 (2009)

    Google Scholar 

  14. Zheng, Ni, L.M.: Smart Phone and Next-Generation Mobile Computing. Morgan Kaufmann Publishers, San Francisco (2006)

    Google Scholar 

  15. Wagner, D., Schmalstieg, D.: History and Future of Tracking for Mobile Phone Augmented Reality. In: International Symposium on Ubiquitous Virtual Reality (ISUVR 2009), pp. 1–4 (2009)

    Google Scholar 

  16. Koch, D., Walther, D., Edgington, C.: Detection and tracking of objects in underwater video. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2004)

    Google Scholar 

  17. Klein, G., Murray, D.W.: Parallel tracking and mapping for small AR workspaces. In: Proceedings of the International Symposium on Mixed and Augmented Reality, ISMAR (2007)

    Google Scholar 

  18. Klein, G., Murray, D.: Parallel tracking and mapping on a camera phone. In: International Symposium on Mixed and Augmented Reality (2009)

    Google Scholar 

  19. Skrypnyk, I., Lowe, D.: Scene modeling, recognition and tracking with invariant image features. In: Proc. of ISMAR 2004, pp. 110–119 (2004)

    Google Scholar 

  20. Davison, A.J., Mayol, W.W., Murray, D.W.: Real-time localization and mapping with wearable active vision. In: Proc. of ISMAR, pp. 18–27 (2003)

    Google Scholar 

  21. Klein, G., Drummond, T.: Robust visual tracking for noninstrumented augmented reality. In: Proc. of ISMAR, pp. 113–122 (2003)

    Google Scholar 

  22. Bleser, G., Stricker, D.: Advanced tracking through efficient image processing and visual-inertial sensor fusion. In: Proc. of IEEE VR, pp. 137–144 (2008)

    Google Scholar 

  23. Lepetit, V., Lagger, P., Fua, P.: Randomized trees for real-time keypoint recognition. In: Proc. CVPR, pp. 775–781 (2005)

    Google Scholar 

  24. Naimark, L., Foxlin, E.: Circular Data Matrix Fiducial System and Robust Image Processing for a Wearable Vision-Inertial Self-Tracker. In: Proceedings of the 1st International Symposium on Mixed and Augmented Reality (ISMAR), pp. 27–36. IEEE Computer Society, Washington, DC (2002)

    Chapter  Google Scholar 

  25. Jiang, B., Neumann, U., Suya, Y.: A robust hybrid tracking system for outdoor augmented reality. In: Proceedings of Virtual Reality, pp. 3–275 (2004)

    Google Scholar 

  26. Hol, J.D., Schon, T.B., Gustafsson, F., Slycke, P.J.: Sensor Fusion for Augmented Reality. In: 9th International Conference on Information Fusion, pp. 1–6 (2006)

    Google Scholar 

  27. Reitmayr, G., Drummond, T.W.: Initialization for Visual Tracking in Urban Environments, pp. 161–172 (2007)

    Google Scholar 

  28. Seo, B.-K., Kim, K., Park, J.: A tracking framework for augmented reality tours on cultural heritage sites. In: 9th ACM SIGGRAPH Conf. on Virtual-Reality Continuum and its Applications in Industry, pp. 169–174 (2010)

    Google Scholar 

  29. Lee, G.A., Yang, U., Kim, Y., Jo, D., Kim, H., Kim, J.H., Choi, J.: Freeze-Set-Go Interaction Method for Handheld Mobile Augmented Reality Environments. In: VRST 2009 Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology, pp. 143–146 (2009)

    Google Scholar 

  30. Seichter, H., Schmalstieg, D.: Handheld augmented reality indoor navigation with activity-based instructions. In: 13th Int’l Conf. on Human-Computer Interaction with Mobile Devices and Services (2011)

    Google Scholar 

  31. Kurkovsky, S., Koshy, R., Novak, V., Szul, P.: Current issues in handheld augmented reality. In: International Conference on Communications and Information Technology (ICCIT), pp. 68–72 (2011)

    Google Scholar 

  32. Siltanen, S.: Theory and applications of marker-based augmented reality (2012)

    Google Scholar 

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Obeidy, W.K., Arshad, H., Ahmad Chowdhury, S., Parhizkar, B., Huang, J. (2013). Increasing the Tracking Efficiency of Mobile Augmented Reality Using a Hybrid Tracking Technique. In: Zaman, H.B., Robinson, P., Olivier, P., Shih, T.K., Velastin, S. (eds) Advances in Visual Informatics. IVIC 2013. Lecture Notes in Computer Science, vol 8237. Springer, Cham. https://doi.org/10.1007/978-3-319-02958-0_41

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  • DOI: https://doi.org/10.1007/978-3-319-02958-0_41

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02957-3

  • Online ISBN: 978-3-319-02958-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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