A new distance measure for non-rigid image matching

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1654, Issue , 1999, Pages 237-252

  Rangarajan, Anand ^a   Chui, Haili ^a   Mjolsness, Eric ^b  

^a YALE UNIVERSITY   (United States)

^b CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; GEOMETRY; GRAPHIC METHODS; IMAGE MATCHING;

DISTANCE MEASURE; GENERATIVE MODEL; NONRIGID MATCHING; POINT CORRESPONDENCE; QUADRATIC ASSIGNMENT; REAL-WORLD; SPLINE KERNELS; WEIGHTED GRAPH;

PATTERN RECOGNITION;

EID: 84958780228     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-48432-9_17     Document Type: Conference Paper

References (33)

1. Y. Amit. Graphical templates for model recognition. IEEE Trans. Patt. Anal. Mach. Intell., 18(4):225–236, 1996.
2. R. Bajcsy and S. Kovacic. Multiresolution elastic matching. Computer Vision, Graphics and Image Processing, 46:1–21, 1989.
3. J. Bernardo and A. Smith. Bayesian Theory. John Wiley and Sons, New York, NY, 1994.
4. P. J. Besl and N. D. McKay. A method for registration of 3-D shapes. IEEE Trans. Patt. Anal. Mach. Intell., 14(2):239–256, Feb. 1992.
5. M. Black and A. Jepson. Estimating optical flow in segmented images using variable-order parametric models and local deformations. IEEE Trans. Patt. Anal. Mach. Intell., 18(10):972–986, 1996.
6. F. L. Bookstein. Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Trans. Patt. Anal. Mach. Intell., 11(6):567–585, June 1989.
7. G. Christensen, S. Joshi, and M. Miller. Volumetric transformation of brain anatomy. IEEE Trans. Med. Imag., 16(6):864–877, 1997.
8. T. Cootes, C. Taylor, D. Cooper, and J. Graham. Active shape models: Their training and application. Computer Vision and Image Understanding, 61(1):38–59, 1995.
9. A. D. J. Cross and E. R. Hancock. Graph matching with a dual-step EM algorithm. IEEE Trans. Patt. Anal. Mach. Intell., 20(11):1236–1253, 1998.
10. J. Feldmar and N. Ayache. Rigid, affine and locally affine registration of free-form surfaces. Intl. J. Computer Vision, 18(2):99–119, May 1996.
11. A. M. Finch, R. C. Wilson, and E. R. Hancock. An energy function and continuous edit process for graph matching. Neural Computation, 10(7):1873–1894, 1998.
12. M. R. Garey and D. S. Johnson. Computers and intractability: a guide to the theory of NP–completeness. W. H. Freeman, San Francisco, CA, 1979.
13. S. Gold and A. Rangarajan. A graduated assignment algorithm for graph matching. IEEE Trans. Patt. Anal. Mach. Intell., 18(4):377–388, 1996.
14. E. Grimson. Object Recognition by Computer: The Role of Geometric Constraints. MIT Press, Cambridge, MA, 1990.
15. T. Hofmann and J. M. Buhmann. Pairwise data clustering by deterministic annealing. IEEE Trans. Patt. Anal. Mach. Intell., 19(1):1–14, Jan. 1997.
16. B. Kim, J. L. Boes, K. A. Frey, and C. R. Meyer. Mutual information for automated unwarping of rat brain autoradiographs. NeuroImage, 5:31–40, 1997.
17. G. Lohmann and D. von Cramon. Sulcal basin and sulcal strings as new concepts for describing the human cortical topography. In Workshop on Biomedical Image Analysis, pages 41–54. IEEE Press, June 1998.
18. D. Metaxas, E. Koh, and N. I. Badler. Multi-level shape representation using global deformations and locally adaptive finite elements. Intl. J. Computer Vision, 25(1):49–61, 1997.
19. E. Mjolsness and C. Garrett. Algebraic transformations of objective functions. Neural Networks, 3:651–669, 1990.
20. H. Ogawa. Labeled point pattern matching by Delaunay triangulations and maximal cliques. Pattern Recognition, 19:35–40, 1986.
21. S. Pappu, S. Gold, and A. Rangarajan. A framework for non-rigid matching and correspondence. In D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, editors, Advances in Neural Information Processing Systems 8, pages 795–801. MIT Press, Cambridge, MA, 1996.
22. M. Pelillo. Replicator equations, maximal cliques and graph isomorphism. Neural Computation, 11, 1999. (in press).
23. S. Sclaroff and A. P. Pentland. Modal matching for correspondence and recognition. IEEE Trans. Patt. Anal. Mach. Intell., 17(6):545–561, Jun. 1995.
24. G. Scott and C. Longuet-Higgins. An algorithm for associating the features of two images. Proc. Royal Society of London, B244:21–26, 1991.
25. L. Shapiro and J. Brady. Feature-based correspondence: an eigenvector approach. Image and Vision Computing, 10:283–288, 1992.
26. L. G. Shapiro and R. M. Haralick. Structural descriptions and inexact matching. IEEE Trans. Patt. Anal. Mach. Intell., 3(9):504–519, Sept. 1981.
27. R. Szeliski and S. Lavallee. Matching 3D anatomical surfaces with non-rigid deformations using octree splines. Intl. J. Computer Vision, 18:171–186, 1996.
28. H. Tagare, D. O’Shea, and A. Rangarajan. A geometric criterion for shape based non-rigid correspondence. In Fifth Intl. Conf. Computer Vision (ICCV), pages 434–439, 1995.
29. S. Umeyama. Parameterized point pattern matching and its application to recognition of object families. IEEE Trans. Patt. Anal. Mach. Intell., 15(1):136–144, Jan. 1993.
30. P. Viola and W. M. Wells III. Alignment by maximization of mutual information. In Fifth Intl. Conf. Computer Vision (ICCV), pages 16–23. IEEE Press, 1995.
31. G. Wahba. Spline models for observational data. SIAM, Philadelphia, PA, 1990.
32. T. Wakahara. Shape matching using LAT and its application to handwritten character recognition. IEEE Trans. Patt. Anal. Mach. Intell., 16(6):618–629, 1994.
33. A. L. Yuille and N. M. Grzywacz. A mathematical analysis of the motion coherence theory. Intl. J. Computer Vision, 3(2):155–175, June 1989.