Abstract
In this paper we present a model-based approach for the real-time recognition and registration for augmented reality applications. It does not need any artificial markers to track the target. What the system need is the 3D model of target and some representative learning images. The most contribution of our work is that we put forward an idea of transferring the construction of correspondent point pairs between model and real scenes to the calculation of the affine matrix between a pair of 2D images. Our method is based on a two-stage process. In the first stage, a set of features is learned from the training images. The second stage matches the learned features with that obtained from the real scenes. If the target is recognized, the final correspondences used for registration are built with the help of the calculated affine matrix. The system is robust to large viewpoint changes and partial occlusions. And in the premise of stability assurance, the system has a good performance in reducing the computation burden.
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References
Azuma, R.T.: A survey of augmented reality. Presence: Teleperations and Virtual Environments 6(4), 355–385 (1997)
Baillot, Y., Behringer, R., Feiner, S., Julier, S., Maclntyre, B., Azuma, R.T.: Recent advances in augmented reality. IEEE Computer Graphics and Application 21(6), 34–47 (2001)
Kato, H., Billinghurst, M., Poupyrev, I.: ARToolKit Manual[M]. Version 2.70. Human Interface Technology Laboratory, University of Washington. washington.edu/artoolkit/, 7 (2005), http://www.hitl
Jurie, F.: Solution of the Simultaneous Pose and Correspondence Problem Using Gaussian Error Model. Computer Vision and Image Understanding 73(3), 357–373 (1996)
Allezard, N., Dhome, M., Jurie, F.: Recognition of 3d textured objects by mixing view-based and model-based representations. In: International Conference on Pattern Recognition, Barcelona, Spain, pp. 960–963 (2000)
Harris, C.G., Stephens, M.J.: A combined corner and edge detector. In: Fourth Alvey Vision Conference, Manchester (1988)
Lowe, D.G.: Object recognition from local scale-invariant features. In: International Conference on Computer Vision, pp. 1150–1157 (1999)
Mikolajczyk, K., Schmid, C.: An affine invariant interest point detector. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 128–142. Springer, Heidelberg (2002)
Baumberg, A.: Reliable feature matching across widely separated views. In: Conference on Computer Vision and Pattern Recognition, pp. 774–781 (2000)
Lepetit, V., Vacchetti, L., Thalmann, D., Fua, P.: Fully Automated and Stable Regis-tration for Augmented Reality Applications. In: Proc. Second IEEE and ACM International Symposium on Mixed and Augmented Reality (2003)
Genc, Y., Riedel, S., Souvannavong, F., Navab, N.: Markerless tracking for aug-mented reality: A learning-based approach. In: Proc. International Symposium on Mixed and Augmented Reality (2002)
Comport, A.I., Marchand, E., Chaumette, F.: A real-time tracker for marker-less augmented reality. In: Proc. Second IEEE and ACM International Symposium on Mixed and Augmented Reality, Tokyo, Japan, pp. 36–45 (2003)
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Ma, Z.Y., Chen, Y.P., Yuan, C.M., Zhou, Z.D. (2006). An Efficient 3D Registration Method Using Markerless Image in AR-Based CNC Machining Simulation. In: Pan, Z., Cheok, A., Haller, M., Lau, R.W.H., Saito, H., Liang, R. (eds) Advances in Artificial Reality and Tele-Existence. ICAT 2006. Lecture Notes in Computer Science, vol 4282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941354_19
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DOI: https://doi.org/10.1007/11941354_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49776-9
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