Abstract
We present a novel technique for the automatic adaptation of a deformable model's elastic parameters within a Kalman filter frame-work for shape estimation applications. The novelty of the technique is that the model's elastic parameters are not constant, but time varying. The model for the elastic parameter variation depends on the local error of fit and the rate of change of the error of fit. By augmenting the state equations of an extended Kalman filter to incorporate these additional variables and take into account the noise in the data, we are able to significantly improve the quality of the shape estimation. Therefore, the model's elastic parameters are initialized always to the same value and they subsequently modified depending on the data and the noise distribution. In addition, we demonstrate how this technique can be parallelized in order to increase its efficiency. We present several experiments to demonstrate the effectiveness of our method.
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References
A. Blake and M. Isard, “3D position, attitude and shape input using video tracking of hands and lips”, Proc. Siggraph'94, pp. 185–192, 1994.
T. Broida and R. Chellappa, “Estimation of object motion parameters from noisy images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(1):90–98, January 1986.
L. D. Cohen. “On Active Contour Models and Balloons”. CVGIP: IU, 53(2), 1991.
C. W. Chen and T. S. Huang, “Epicardial Motion and Deformation Estimation from Coronary Artery Bifurcation Points”, IEEE Proc. Third International Conference on Computer Vision (ICCV '90), pp. 456–459, Osaka, Japan, Dec. 1990.
E. D. Dickmanns and Volker Graefe, “Dynamic Monocular Machine Vision”, Machine Vision and Applications, 1:223–240, 1988.
J. S. Duncan and R. L. Owen and P. Anandan, “Measurement of Nonrigid Motion Using Contour Shape Descriptors”, IEEE Computer Vision and Pattern Recognition Conference (CVPR'91), pp. 318–324, Hawaii, 1991.
A. Gelb. “Applied Optimal Estimation”, MIT Press, Cambridge, MA, 1974.
M. S. Grewal and A. P. Andrews. Kalman Filtering: Theory and Applications. Prentice Hall, 1993.
D. B. Goldgof and H. Lee and T. S. Huang, “Motion Analysis of Nonrigid Structures”, IEEE Computer Vision and Pattern Recognition Conference (CVPR'88), pp. 375–380, 1988.
T. S. Huang, “Modeling, Analysis and Visualization of Nonrigid Object Motion”, IEEE 10th International Conference on Pattern Recognition, Atlantic City, NJ, pp. 361–364, 1990.
M. Kass and A. Witkin and D. Terzopoulos, “Snakes: Active Contour Models”, International Journal of Computer Vision, 1(4), pp. 321–331, 1988.
I. A. Kakadiaris and D. Metaxas, 3D Human Body Model acquisition from Multiple views, Proc. ICCV'95, pp. 618–623, June 20–23, Boston, MA, 1995.
O. V. Larsen, P. Radeva, and E. Marti, Guidelines for choosing optimal parameters of elasticity for snakes, 6th International Conference on Computer Analysis of Images and Patterns, pp. 106–113, Praga, 1995.
L. Matthies, T. Kanade, and R. Szeliski, “Kalman Filter-based Algorithms for Estimating Depth from Image Sequences”, International Journal of Computer Vision, 3:209–236, 1989.
D. Metaxas and D. Terzopoulos. Recursive Estimation of Nonrigid Shape and Motion. Proc. IEEE Motion Workshop, Princeton, NJ, pp. 306–311, October 1991.
D. Metaxas and D. Terzopoulos. Shape and Nonrigid Motion Estimation Through Physics-Based Synthesis. IEEE Trans. Pattern Analysis and Machine Intelligence, June, 1993.
D. Metaxas and E. Koh. “Flexible Multibody Dynamics and Adaptive Finite Element Techniques for Model Synthesis and Estimation” Computer Methods in Applied Mechanics and Engineering, in press.
A. Pentland and B. Horowitz, “Recovery of Non-rigid Motion and Structure”, IEEE Trans. Pattern Analysis and Machine Intelligence, 13(7):730–742, 1991.
R. Samadani. Adaptive Snakes: Control of damping and material parameters. SPIE Geometric Methods in Computer Vision, Vol 1570, 1991.
O. Zienkiewicz. The Finite Element Method. McGraw-Hill, 1977.
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© 1996 Springer-Verlag Berlin Heidelberg
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Metaxas, D., Kakadiaris, I.A. (1996). Elastically adaptive deformable models. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1065. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61123-1_169
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DOI: https://doi.org/10.1007/3-540-61123-1_169
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