Metamorphs: Deformable shape and appearance models

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 30, Issue 8, 2008, Pages 1444-1459

  Huang, Xiaolei ^a   Metaxas, Dimitris N ^b  

^a Lehigh University   (United States)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

Appearance; Boundary; Deformable models; Distance transform; Edge; Free form deformations; Implicit shape representation; Level set; Nonparametric intensity statistics; Region; Segmentation; Shape

Indexed keywords

APPEARANCE MODELING; BOUNDARY SHAPES; DEFORMABLE MODELING; DIMENSIONAL SPACES; DISTANCE MAPS; DISTANCE TRANSFORMS; FREE FORM DEFORMATIONS (FFD); METAMORPHS;

DEFORMATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THEORETICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 46149086158     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.70795     Document Type: Article

References (50)

1. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active Contour Models," Int'l J. Computer Vision, vol. 1, pp. 321-331, 1987.
2. L.H. Staib and J.S. Duncan, "Boundary Finding with Parametrically Deformable Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 11, pp. 1061-1075, Nov. 1992.
3. L.D. Cohen and I. Cohen, "Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D images," IEEE Trans. Pattern Analysis and Machine intelligence, vol. 15, pp. 1131-1147, 1993.
4. V. Caselles, R. Kimmel, and G. Sapiro, "Geodesic Active Contours," Proc. Fifth, IEEE Int'l Conf. Computer Vision, pp. 694-699, 1995.
5. R. Malladi, J. Sethian, and B. Vemuri, "Shape Modeling with Front Propagation: A Level Set Approach," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 2, pp. 158-175, Feb. 1995.
6. T.F. Cootes, C.J. Taylor, D.H. Cooper, and J. Graham, "Active Shape Models - Their Training and Application," Computer Vision and image Understanding, vol. 61, no. 1, pp. 38-59, 1995.
7. T.F. Cootes, G.J. Edwards, and C.J. Taylor, "Active Appearance Models," Proc. Fifth European Conf. Computer Vision, vol. 2, pp. 484-498, 1998.
8. M.E. Leventon, E.L. Grimson, and O. Faugeras, "Statistical Shape influence in Geodesic Active Contours," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 1316-1323, 2000.
9. D. Metaxas, Physics-Based Deformable Models. Kluwer Academic, 1996.
10. T. McInerney and D. Terzopoulos, "A Dynamic Finite Element Surface Model for Segmentation and Tracking in Multidimensional Medical images with Application to Cardiac 4D Image Analysis," Computerized Medical Imaging and Graphics, vol. 19, no. 1, pp. 69-83, 1995.
11. C. Xu and J.L. Prince, "Snakes, Shapes and Gradient Vector Flow," IEEE Trans. Image Processing, vol. 7, no. 3, pp. 359-369, 1998.
12. A. Yezzi, S. Kichenssamy, A. Kumar, P. Olver, and A. Tannebaum, "A Geometric Snake Model for Segmentation of Medical Imagery," IEEE Trans. Medical Imaging, vol. 16, no. 2, pp. 199-209, 1997.
13. T. Chan and L. Vese, "Active Contours without Edges," IEEE Trans. Image Processing, vol. 10, no. 2, pp. 266-277, 2001.
14. R. Ronfard, "Region-Based Strategies for Active Contour Models," Int'l J. Computer Vision, vol. 13, no. 2, pp. 229-251, 1994.
15. S. Zhu and A. Yuille, "Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multi-Band image Segmentation," IEEE Trans. Pattern Analysis and Machine intelligence, vol. 18, no. 9. pp. 884-900, Sept. 1996.
16. T. Jones and D. Metaxas, "Automated 3D Segmentation Using Deformable Models and Fuzzy Affinity," Proc. 15th Int'l Cont. Information Processing in Medical imaging, pp. 113-126, 1997.
17. T. Chen and D. Metaxas, "Image Segmentation Based on the Integration of Markov Random Fields and Deformable Models," Proc. Third Int'l Conf. Medical Imaging Computing and Computer-Assisted Intervention, pp. 256-265, 2000.
18. R. Huang, V. Pavlovic, and D. Metaxas, "A Graphical Model Framework for Coupling MRFS and Deformable Models," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 739-746, 2004.
19. S. Jehan-Besson, M. Barlaud, and G. Aubert, "Shape Gradients for Histogram Segmentation Using Active Contours," Proc. Ninth IEEE Int'l Conf. Computer Vision, pp. 408-415, 2003.
20. G. Aubert, M. Barland, O. Faugeras, and S. Jehan-Besson, "Image Segmentation Using Active Contours: Calculus of Variations or Shape Gradients," SIAM Applied Math., vol. 63, no. 6, pp. 2128-2154, 2003.
21. A.J. Yezzi, A. Tsai, and A. Willsky, "A Statistical Approach to Snakes for Bimodal and Trimodal Imagery," Proc. Fifth IEEE Int'l Conf. Computer Vision, vol. 2, pp. 898-903, 1999.
22. C. Samson, L. Blanc-Feraud, G. Aubert, and J. Zerubia, "A Level Set Model for image Classification," Int'l J. Computer Vision, vol. 40, no. 3, pp. 187-198, 2000.
23. L.A. Vese and T.F. Chan, "A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Modal," Int'l J. Computer Vision, vol. 50, no. 3, pp. 271-293, 2002.
24. N. Paragios and R. Deriche, "Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation," Int'l J. Computer Vision, vol. 46, no. 3, pp. 223-247, 2002.
25. D. Mumford and J. Shah, "Optimal Approximations by Piecewise Smooth Functions and Associated Variational Problems," Comm. Pure and Applied Math., vol. 42, no. 5, pp. 577-685, 1989.
26. A. Eigammal, R. Duraiswami, and L.S. Davis, "Efficient Kernel Density Estimation Using the Fast Gauss Transform With Applications to Color Modeling and Tracking," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 11, pp. 1499-1504, Nov. 2003.
27. D. Comaniciu and P. Meer, "Mean Shift: A Robust Approach toward Feature space, Analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 603-619, May 2002.
28. A.A. Amini, Y. Chen, M. Elayyadi, and P. Radeva, "Tag Surface Reconstruction and Tracking of Myocardial Beads from SPAMM-MRI with Parametric B-Spline Surfaces," IEEE Trans. Medical Imaging, vol. 20, no. 2, pp. 94-103, 2001.
29. P. Faloutsos, M. van de Panne, and D. Terzopoulos, "Dynamic Free-Form Deformations for Animation Synthesis," IEEE Trans. Visualization and Computer Graphics, vol. 3, pp. 201-214, 1997.
30. S. Osher and J. Sethian, "Fronts Propagating with Curvature-Dependent Speed: Algorithms Based on the Hamilton-Jacobi Formulation," J. Computational Physics, vol. 79, pp. 12-49, 1988.
31. T.W. Sederberg and S.R. Parry, "Free-Form Deformation of Solid Geometric Models," Proc. 13th Ann. Conf. Computer Graphics, pp. 151-160, 1986.
32. X. Huang, N. Paragios, and D. Metaxas, "Shape Registration in implicit Spaces Using information Theory and Free-Form Deformations," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 8, pp. 1303-1318, Aug. 2006.
33. Y.S. Akgul and C. Kambhamettu, "A Coarse-to-Fine Deformable Contour Optimization Framework," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25 no. 2, pp. 174-186, Feb. 2003.
34. R.O. Duda and P. Hart, Pattern Classification and Scene Analysis. Wiley, 1973.
35. D.W. Scott, Multivariate Density Estimation. Wiley-Interscience, 1992.
36. A. Elgammal, D. Harwood, and L.S. Davis, "Non-Parametric Model for Background Subtraction," Proc. Sixth European Conf. Computer Vision pp. 751-767, 2000.
37. R.M. Haralick and L. Shapiro, Computer and Robot Vision. Addison-Wesley, 1992.
38. N. Govindaraju, D. Knott, N. Jain, I. Kabul, R. Tamstorf, R. Gayle, M. Lin, and D. Manocha, "Interactive Collision Detection between Deformable Models Using Chromatic Decomposition," ACM Trans. Graphics, vol 24, no. 3, pp. 991-999, 2005.
39. X. Huang, Z. Qian, R. Huang, and D. Metaxas, "Deformable-Model Based Textured Object Segmentation," Proc. Fourth Int'l Workshop Energy Minimization Methods in CVPR, pp. 119-135, 2005.
40. L. Wolf, X. Huang, I. Martin, and D. Metaxas, "Patch-Based Texture Edges and Segmentation," Proc. Ninth European Conf. Computer Vision pp. 481-493, 2006.
41. M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis and Machine Vision, second ed. PWS Publishing, 1999.
42. M. Berthod, Z. Kato, S. Yu, and J. Zerubia, "Bayesian Image Classification Using Markov Random Fields," Image and Vision Computing, vol. 14, pp. 285-295, 1996.
43. J. Shi and J. Malik, "Normalized Cuts and Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 888-905, Aug. 2000.
44. A. Chakraborty, L. Staib, and J. Duncan, "Deformable Boundary Finding in Medical Images by Integrating Gradient and Region Information," IEEE Trans. Medical Imaging, vol. 15, no. 6, pp. 859-870, 1996.
45. A. Chakraborty and J.S. Duncan, "Game-Theoretic Integration for Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence vol. 21, no. 1, pp. 12-30, Jan. 1999.
46. K. Karantzalos and N. Paragios, "Implicit Free-Form-Deformations for Multi-Frame Segmentation and Tracking," Proc. Fourth IEEE Workshop Variational, Geometric, and Level Set Methods in Computer Vision, 2005.
47. N. Paragios, "Geodesic Active Regions and Level Set Methods: Contributions and Applications in Artificial Vision," PhD dissertation, School of Computer Eng., Univ. of Nice Sophia Antipolis, 2000.
48. H.X.C. Xu and J.L. Prince, "A Topology Preserving Level Set Method for Geometric Deformable Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 6, pp. 755-768, June 2003.
49. X. Huang, Z. Li, and D. Metaxas, "Learning Coupled Prior Shape and Appearance Models for Segmentation," Proc. Seventh Int'l Conf. Medical Imaging Computing and Computer-Assisted Intervention, vol. 1, pp. 60-69, 2004.
50. D. Martin, C. Fowlkes, D. Tal, and J. Malik, "A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics," Proc. Seventh IEEE Int'l Conf. Computer Vision, vol. 2, pp. 416-423, 2001.