Abstract
A new deformable shape model is defined with the following properties: [1] A-priori knowledge describes shapes not only by statistical variation of a fixed structure like active shape/appearance model but also by variability of structure using a production system. [2] Multi-resolution description of shape structures enable more constrained statistical variation of shape as the model evolves in fitting the data. [3] It enables comparison between different shapes as well as characterizing and reconstructing instances of the same shape. Experiments on simulated 2D shapes demonstrate the ability of the algorithm to find structures of different shapes and also to characterize the statistical variability between instances of the same shape.
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References
Cootes, T., Taylor, C.: Statistical Models of Appearance for Medical Image Analysis and Computer Vision. Proceedings of SPIE in Medical Imaging: ImageProcessiong, Vol. 4322 (2001) 236–248.
Mitchell, S., Lelieveldt, B., van der Geest, R., Bosch, H., Reiber, J., Sonka, M.: Time Continuous Segmentation of Cardiac MR Image Sequences using Active Appearance Motion Models. Proceedings of SPIE in Medical Imaging: ImageProcessiong, Vol. 4322 (2001) 249–256.
Chen M.: 3-D Deformable Registration Using a Statistical Atlas with Applications in Medicine. MICCAI (1999) 621–630.
Malladi, R., Sethian, J., Vemuri, B.: Shape Modeling with Front Propagation: A Level Set Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17(2). (1995) 158–175.
Szeliski, R., Tonnesen, D., Terzopoulos, D.: Modeling Surfaces of Arbitrary Topology with Dynamic particles. Proc. Computer Vision and Vision Recognition (CVPR) (1993) 82–87.
McInerney, T., Terzopoulos, D.: Topology Adaptive Deformable Surfaces for Medical Image Volume Segmentation. IEEE Transactions on Medical Imaging, Vol. 18(9). (1999) 100–111.
Siddiqi, K., Kimia, B.: Toward a Shock Grammar for Recognition. IEEE Conf. on Computer Vision and Pattern Recognition, 1996.
Pentland, A., Sclaroff, S.: Closed-Form Solutions for Physically Based Shape Modeling and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13(7). (1991) 715–729.
Terzopoulos, D., Metaxas, D.: Dyanamic 3D Models with Local and Global Deformations: Deformable Superquadrics. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13(7). (1991) 703–714.
DeCarlo, D., Metaxas, D.: Shape Evolution with Structural and Topological Changes using Blending. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20(11). (1998) 1186–1205.
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© 2002 Springer-Verlag Berlin Heidelberg
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Al-Zubi, S., Tönnies, K. (2002). Extending Active Shape Models to Incorporate a-priori Knowledge about Structural Variability. In: Van Gool, L. (eds) Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, vol 2449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45783-6_41
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DOI: https://doi.org/10.1007/3-540-45783-6_41
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