Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Towards a General Multi-View Registration Technique
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rigid, affine and locally affine registration of free-form surfaces
International Journal of Computer Vision
A Framework for Uncertainty and Validation of 3-D RegistrationMethods Based on Points and Frames
International Journal of Computer Vision
Shock Graphs and Shape Matching
International Journal of Computer Vision
Shape Similarity Measure Based on Correspondence of Visual Parts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Registration and integration of textured 3-D data
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Non-rigid registration using distance functions
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Three-dimensional shape knowledge for joint image segmentation and pose estimation
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Combined Registration Methods for Pose Estimation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Visual quality control of planar working pieces: a curve based approach using prototype fitting
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part IV
Shape retrieval and recognition on mobile devices
MUSCLE'11 Proceedings of the 2011 international conference on Computational Intelligence for Multimedia Understanding
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In this paper, we analyze two conceptionally different approaches for shape matching: the well-known iterated closest point (ICP) algorithm and variational shape registration via level sets. For the latter, we suggest to use a numerical scheme which was introduced in the context of optic flow estimation. For the comparison, we focus on the application of shape matching in the context of pose estimation of 3-D objects by means of their silhouettes in stereo camera views. It turns out that both methods have their specific shortcomings. With the possibility of the pose estimation framework to combine correspondences from two different methods, we show that such a combination improves the stability and convergence behavior of the pose estimation algorithm.