A graph-spectral method for surface height recovery

Pattern Recognition

Volumn 38, Issue 8, 2005, Pages 1167-1186

  Robles Kelly, Antonio ^a   Hancock, Edwin R ^b  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b UNIVERSITY OF YORK   (United Kingdom)

Author keywords

Curvature; Markov chain; Surface normals; Surface reconstruction

Indexed keywords

ALGORITHMS; DATA ACQUISITION; EIGENVALUES AND EIGENFUNCTIONS; IMAGE RECONSTRUCTION; MARKOV PROCESSES; NUMERICAL METHODS; OPTIMIZATION; SENSITIVITY ANALYSIS; VECTORS;

CURVATURE; GRAPH-SPECTRAL METHOD; SURFACE NORMALS; SURFACE RECONSTRUCTION;

GRAPH THEORY;

EID: 18544368218     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2004.12.005     Document Type: Article

References (42)

1. A.P. Rockwood, and J. Winget Three-dimensional object reconstruction from two dimensional images Computer-Aided Des. 29 4 1997 279 285
2. B.K.P. Horn, and M.J. Brooks The variational approach to shape from shading CVGIP 33 2 1986 174 208
3. B.K.P. Horn Height and gradient from shading Int. J. Comput. Vision 5 1 1990 37 75
4. Z. Wu, and L. Li A line-integration based method for depth recovery from surface normals CVGIP 43 1 1988 53 66
5. A.G. Bors, E.R. Hancock, and R.C. Wilson Terrain analysis using radar shape-from-shading IEEE Trans. Pattern Anal. Mach. Intell. 25 8 2003 974 992
6. P. Dupuis, J. Oliensis, Direct method for reconstructing shape from shading, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1992, pp. 453-458.
7. M. Bichsel, A.P. Pentland, A simple algorithm for shape from shading, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1992, pp. 459-465.
8. Y.G. Leclerc, A.F. Bobick, The direct computation of height from shading, in: Proceedings of Computer Vision and Pattern Recognition, 1991, pp. 552-558.
9. P.S. Tsai, and M. Shah Shape from shading using linear approximation Image Vision Comput. 12 8 1994 487 498
10. B. Karaçali, and W. Snyder Reconstructing discontinuous surfaces from a given gradient field using partial integrability Comput. Vision Image Understanding 92 1 2003 78 111
11. B. Karaçali, and W. Snyder Noise reduction in surface reconstruction from a given gradient field Int. J. Comput. Vision 60 1 2004 25 44
12. R. Kimmel, K. Siddiqqi, B.B. Kimia, A.M. Bruckstein, Shape from shading: level set propagation and viscosity solutions, Int. J. Comput. Vision (16) (1995) 107-133.
13. R. Kimmel, and A.M. Bruckstein Tracking level sets by level sets a method for solving the shape from shading problem Comput. Vision Image Understanding 62 2 1995 47 48
14. R.T. Frankot, and R. Chellappa A method of enforcing integrability in shape from shading algorithms IEEE Trans. Pattern Anal. Mach. Intell. 4 10 1988 439 451
15. L. Noakes, R. Kozera, R. Klette, The lawn-moving algorithm for noisy gradient vector fields, in: Proceedings of SPIE Conference, Vision Geometry VIII, 1999, pp. 305-316.
16. T. Wei, R. Klette, Depth recovery from noisy gradient vector fields using regularization, in: CAIP, 2003, pp. 116-123.
17. R. Zhang, P.S. Tsai, J.E. Cryer, and M. Shah Shape from shading a survey IEEE Trans. Pattern Anal. Mach. Intell. 21 8 1999 690 706
18. J. Shi, and J. Malik Normalized cuts and image segmentation IEEE Trans. Pattern Anal. Mach. Intell. 22 8 2000 888 905
19. S. Sarkar, and K.L. Boyer Quantitative measures of change based on feature organization eigenvalues and eigenvectors Comput. Vision and Image Understanding 71 1 1998 110 136
20. P. Perona, W.T. Freeman, Factorization approach to grouping, in: Proceedings ECCV, 1998, pp. 655-670.
21. N.L. Biggs Algebraic Graph Theory 1993 Cambridge University Press Cambridge
22. L. Lovász Random walks on graphs a survey Bolyai Soc. Math. Stud. 2 2 1993 1 46
23. F.R.K. Chung Spectral Graph Theory 1997 American Mathematical Society Providence, RI
24. D. Cvetković, M. Doob, and H. Sachs Spectra of Graphs Theory and Application 1980 Academic Press New York
25. A. Sinclair, and M. Jerrum Approximate counting, uniform generation and rapidly mixing Markov chains Inform. Comput. 82 1989 93 133
26. Y. Azar, A. Fiat, A.R. Karlin, F. McSherry, J. Saia, Spectral analysis of data, in: ACM Symposium on Theory of Computing, 2000, pp. 619-626.
27. J. Kleinberg, Authoritative sources in a hyperlinked environment, in: Proceedings ACM-SIAM Symposium on Discrete Algorithms, 1998, pp. 668-677.
28. A. Robles-Kelly, and E.R. Hancock A graph-spectral approach to shape-from-shading IEEE Trans. Image Process. 13 7 2004 912 926
29. A. Robles-Kelly, E.R. Hancock, A graph-spectral method for surface height recovery from needle maps, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, vol. I 2001, pp. 141-148.
30. A. Robles-Kelly, E.R. Hancock, A graph-spectral approach to surface segmentation, in: International Conference on Pattern Recognition, vol. III, 2002, pp. 509-512.
31. A. Robles-Kelly, E.R. Hancock, Edit distance from graph spectra, in: International Conference on Computer Vision, 2003, pp. 234-241.
32. A. Robles-Kelly, E.R. Hancock, String edit distance, random walks and graph matching, in: SSPR 2002, Lecture Notes in Computer Science, vol. 2396, Springer, Berlin, 2002, pp. 104-112.
33. M.P. Do Carmo Differential Geometry of Curves and Surfaces 1976 Prentice-Hall Englewood Cliffs, NJ
34. J.A.F. Leite, and E.R. Hancock Iterative curve organisation with the em algorithm Pattern Recognition Lett. 18 1997 143 155
35. S.W. Zucker, C. David, A. Dobbins, L. Iverson, The organization of curve detection: coarse tangent fields and fine spline coverings, in: Proceedings of the IEEE International Conference on Computer Vision, 1988, pp. 568-577.
36. L.R. Williams, and D.W. Jacobs Stochastic completion fields a neural model of illusory contour shape and salience Neural Comput. 9 4 1997 837 858
37. R.S. Varga Matrix Iterative Analysis second ed. 2000 Springer Berlin
38. B.K.P. Horn Robot Vision 1986 Mc-Graw Hill New York
39. R. Klette, K. Schluns, and A. Koschan Computer Vision Three-Dimensional Data from Images 2001 Springer Singapore
40. P.L. Worthington, and E.R. Hancock New constraints on data-closeness and needle map consistency for shape-from-shading IEEE Trans. Pattern Anal. Mach. Intell. 21 12 1999 1250 1267
41. E.R. Hancock, and J.V. Kittler Discrete relaxation Pattern Recognition 23 1990 711 733
42. D. Mumford, and J. Shah Optimal approximations by piecewise smooth functions and associated variational problems Comm. Pure Appl. Math. 42 5 1989 577 685