Abstract
In this paper we present a new approach that uses local structural information to find correspondences between image and model contour information. For a monocular pose estimation scenario, the pose is computed by our purposed new variant of the ICP (iterative closest point) algorithm which combines Euclidean distance with structure. A local representation of 3D free-form contours is used to get the structural information in 3D space and in the image plane. Furthermore, the local structure of free-form contours is combined with local orientation and phase obtained from the monogenic signal. With this combination, we achieve a more robust correspondence search. Our approach was tested on synthetical and real data to compare the convergence and performance of our approach against the classical ICP approach.
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Chavarria, M.A., Sommer, G. (2008). Local Structure to Solve the Correspondence Search Problem in a Monocular Pose Estimation Scenario. In: Braz, J., Ranchordas, A., Araújo, H.J., Pereira, J.M. (eds) Computer Vision and Computer Graphics. Theory and Applications. VISIGRAPP 2007. Communications in Computer and Information Science, vol 21. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89682-1_15
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DOI: https://doi.org/10.1007/978-3-540-89682-1_15
Publisher Name: Springer, Berlin, Heidelberg
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