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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© 2006 Springer-Verlag Berlin Heidelberg
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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
Online ISBN: 978-3-540-49779-0
eBook Packages: Computer ScienceComputer Science (R0)