Abstract
Real-time camera tracking in previously unknown scene is attractive to a wide spectrum of computer vision applications. In Recent years, Simultaneous Localization and Mapping (SLAM) system and its varieties have shown extraordinary camera tracking performance. However, the robustness of these systems to rapid and erratic camera motion is still limited because of the typically used Local Localization scheme. To overcome this limitation, we present an efficient online camera tracking algorithm using a Global Localization scheme which matches features in a global way through two steps: First, coarse matches are obtained through nearest feature descriptor search. Afterwards, a Game Theoretic approach is exploited to eliminate the incorrect matches and the left correct matches can be used to estimate the camera pose. Result shows our camera tracking algorithm has significantly improved the robustness of camera tracking system to rapid and erratic camera motion.
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References
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004), ISBN: 0521540518
Wong, K.Y.K., Cipolla, R.: Structure and motion from silhouettes. In: Proceedings of the 8th IEEE International Conference on Computer Vision (ICCV 2001), vol. 2, pp. 217–222 (2001)
Pollefeys, M., Gool, L.V., Vergauwen, M.F.V., Cornelis, K., Tops, J., Koch, R.: Visual modeling with a handheld camera. International Journal of Computer Vision 59, 207–232 (2004)
Davison, A., Reid, I., Molton, N., Stasse, O.: Monoslam: Real-time single camera slam. IEEE Trans. Pattern Analysis and Machine Intelligence 29, 1052–1067 (2007)
Chekhlov, D., Pupilli, M., Mayol-Cuevas, W., Calway, A.: Real-time and robust monocular slam using predictive multi-resolution descriptors. In: Proceedings of the 2nd International Symposium on Visual Computing, pp. 276–285 (2006)
Williams, B., Klein, G., Reid, I.: Real-time slam relocalisation. In: Proceedings of 11th IEEE International Conference on Computer Vision (ICCV 2007), pp. 1–8 (2007)
Eade, E., Drummon, T.: Scalable monocular slam. In: Proceedings of IEEE Intl. Conference on Computer Vision and Pattern Recognition (CVPR 2006), pp. 469–476 (2006)
Klein, G., Murray, D.: Parallel tracking and mapping for small ar workspaces. In: Proceedings of International Symposium on Mixed and Augmented Reality (ISMAR 2007), pp. 1–10 (2007)
Klein, G., Murray, D.: Improving the agility of keyframe-based slam. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. LNCS, vol. 5303, pp. 802–815. Springer, Heidelberg (2008)
Dong, Z.L., Zhang, G.F., Jia, J.Y., Bao, H.J.: Keyframe-based real-time camera tracking. In: Proceedings of IEEE International Conference on Computer Vision (ICCV 2009), pp. 1538–1545 (2009)
Se, S., Lowe, D., Little, J.: Vision-based global localization and mapping for mobile robots. IEEE Transactions on Robotics 21, 364–375 (2005)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–100 (2004)
Calonder, M., Lepetit, V., Fua, P.: Keypoint signatures for fast learning and recognition. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 58–71. Springer, Heidelberg (2008)
Lepetit, V., Fua, P.: Keypoint recognition using randomized trees. Transactions on Pattern Analysis and Machine Intelligence 28, 1465–1479 (2006)
Ozuysal, M., Fua, P., Lepetit, V.: Fast keypoint recognition in ten lines of code. In: Proceedings of 20th Conference on Computer Vision and Pattern Recognition (CVPR 2007), pp. 1–8 (2007)
Ozuysal, M., Calonder, M., Lepetit, V., Fua, P.: Fast keypoint recognition using random ferns. IEEE Transactions on Pattern Analysis and Machine Intelligence 32, 448–461 (2010)
Calonder, M., Lepetit, V., Fua, P.: Pareto-optimal dictionaries for signatures. In: Proceedings of 23rd Conference on Computer Vision and Pattern Recognition, CVPR 2010 (2010)
Bay, H., Ess, A., Tuytelaars, T., Gool, L.V.: Surf: Speeded up robust features. Computer Vision and Image Understanding (CVIU) 110, 346–359 (2008)
Fischler, A.M., Bolles, C.R.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24, 381–395 (1981)
Albarelli, A., Rodol, E., Torsello, A.: A game-theoretic approach to fine surface registration without initial motion estimation. In: Proceedings of 23rd Conference on Computer Vision and Pattern Recognition, CVPR 2010 (2010)
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Yiming, Y., Xiaohui, L., Chen, L., Jie, L. (2011). Real-Time Camera Tracking Using a Global Localization Scheme. In: Koch, R., Huang, F. (eds) Computer Vision – ACCV 2010 Workshops. ACCV 2010. Lecture Notes in Computer Science, vol 6469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22819-3_3
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DOI: https://doi.org/10.1007/978-3-642-22819-3_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22818-6
Online ISBN: 978-3-642-22819-3
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