Motion estimation with quadtree splines

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 18, Issue 12, 1996, Pages 1199-1210

  Szeliski, Richard ^a   Shum, Heung Yeung ^a  

^a MICROSOFT   (United States)

Author keywords

Hierarchical basis functions; Image pyramids; Image registration; Local parametric motion models; Motion analysis; Motion segmentation; Multiresolution analysis; Optical flow; Quadtrees; Splines

Indexed keywords

ALGORITHMS; FUNCTIONS; MATHEMATICAL MODELS; OPTICAL CORRELATION; OPTICAL FLOWS; PARAMETER ESTIMATION; TOPOLOGY; TREES (MATHEMATICS);

ADAPTIVE HIERARCHICAL BASIS SPLINES; IMAGE PYRAMIDS; IMAGE REGISTRATION; LOCAL PARAMETRIC MOTION MODELS; MOTION ANALYSIS; MOTION SEGMENTATION; MULTIRESOLUTION ANALYSIS; QUADTREE SPLINES;

IMAGE SEGMENTATION;

EID: 0030395961     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.546257     Document Type: Article

References (65)

1. E.H. Adelson and J.R. Bergen Spatiotemporal Energy Models for the Perception of Motion J. Optical Soc. Am. vol. A2 no. 2 pp. 284-299 Feb.1985.
2. J.K. Aggarwal and N. Nandhakumar On the Computation of Motion from Sequences of Images-a Review Proc. IEEE vol. 76 no. 8 pp. 917-935 Aug. 1988.
3. P. Anandan A Computational Framework and an Algorithm for the Measurement of Visual Motion Inl'l J. Computer Vision vol. 2 no. 3 pp. 283-310 Jan. 1989.
4. O. Axelsson and V.A. Barker Finite Element Solution of Boundary Value Problems: Theory and Computation. Orlando Fla.: Academic Press 1984.
5. S.T. Barnard and M.A. Fischler Computational Stereo Computing Surveys vol. 14 no. 4 pp. 553-572 Dec. 1982.
6. J.L. Barren D.J. Fleet and S.S. Beauchemin Performance of Optical Flow Techniques Int'l J Computer Vision vol. 12 no. 1 pp. 43-77 Jan. 1994.
7. J.R. Bergen P. Anandan K.J. Hanna and R. Hingorani Hierarchical Model-Based Motion Estimation Second European CoJ. Computer Vision (ECCV'92) pp. 237-252 Santa Margherita Liguere Italy May 1992 Springer-Verlag.
8. MJ. Black and P. Ananclan A Framework for the Robust Estimation of Optic Flow. Fourth Int'l Conf. Computer Vision (ICCV'93) pp. 231-236 Berlin Germany May 1993 IEEE CS Press.
9. MJ. Black and A. Rangarajan The Outlier Process: Unifying Line Processes and Robust Statistics IEEE CS Conf. Computer Vision and Pattern Recognition (CVPR'94) pp. 15-22 Seattle Washington June 1994 IEEE CS Press.
10. M. Bober and J. Kittler Estimation of Complex Multimodal Motion: An Approach Based on Robust Statistics and Hough Transform/'. British Machine Vision Conf. pp. 239-248 1993 BMVA Press.
11. R.C. Holies H.H. Baker and D.H. Marimont Epipolar-Plane Image Analysis: An Approach to Determining Structure from Motion Int'l J. Computer Vision vol. 1 pp. 7-551987.
12. L.G. Brown A Survey of Image Registration Techniques Computing Surveys vol. 24 no. 4 pp. 325-376 Dec. 1992.
13. P.J. Burt and E.H. Adelson The Laplacian Pyramid as a Compact Image Code IEEE Trans. Comm. vol. 31 no. 4 pp. 532-540 Apr. 1983.
14. T.M. Chin M.R. Luettgen W.C. Karl and A.S. Willsky An Estimation-Theoretic Perspective un Image Processing and the Calculation of Optic Flow Advances in Image Sequence Processing. Kluwer 1993.
15. U.R. Dhond and J.K. Aggarwal Structure from Stereo-a Review IEEE Trans. Systems Man and Cybernetics vol. 19 no. 6 pp. 1489-1510 Nov./Dec. 1989.
16. W. Enkelmann Investigations of Multigrid Algorithms for Estimation of Optical Flow Fields in Image Sequences Computer Vision Graphics and Image Processing pp. 150-1771988.
17. M. Eton and Y. Shirai Segmentation and 2D Motion Estimation by Region Fragments Fourth Int'l Conf. Computer Vision (ICCV'93) pp. 192-199 Berlin Germany May 1993 IEEE CS Press.
18. D. Fleet and A. Jepson Computation of Component Image Velocity from Local Phase Information Int'l J. Computer Vision vol. 5 pp. 77-1041990.
19. C.-S. Fuh and P. Maragos Motion Displacement Estimation Using an Affine Model for Image Matching Optical Eng. vol. 30 no. 7 pp. 881-887 July 1991.
20. D. Geiger and F. Girosi Mean Field Theory for Surface Reconstruction IEEE Trans. Pattern Analysis and Machine Intelligence vol. 13 no. 5 pp. 401-412 May 1991.
21. M.A. Gennert Brightness-Based Stereo Matching Second Int'l Conf. Computer Vision (ICCV'88) pp. 139-143 Tampa Florida Dec. 1988 IEEE CS Press.
22. D.J. Heeger Optical Flow from Spatiotemporal Filters First Int'l Conf. Computer Vision (ICCV'87) pp. 181-190 London June 1987 IEEE CS Press.
23. B.C. Hildreth Computing the Velocity Field Along Contours N.I. Badler and J.K. Tsotsos eds. Motion: Representation and Perception. New York: North-Holland 1986 pp. 121-127.
24. B.K.P. Horn and B.G. Schunck Determining Optical Flow Artificial Intelligence vol. 17 pp. 185-2031981.
25. M. Irani B. Rousso and S. Peleg Detecting and Tracking Multiple Moving Objects Using Temporal Integration Second European Conf. Computer Vision (ECCV'92) pp. 282-287 Santa Margherita Liguere Italy May 1992 Springer-Verlag.
26. A. Jepson and MJ. Black Mixture Models for Optical Flow Computation IEEE CS Conf. Computer Vision ana Pattern Recognition (CVPR'93) pp. 760-761'New York June 1993.
27. G. Kùneldorf and G. Wahba ''A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines Annals of Math. Statistics vol. 41 no. 2 pp. 495-5021970.
28. S. Lavallée R. Szeliski and L. Brunie Matching 3-D Smooth Surfaces with Their 2-D Projections Using 3-D Distance Maps SPIE vol. 1570 Geometric Methods in Computer Vision pp. 322-336 San Diego July 1991 Soc. Photo-Optical Instrumentation Eng.
29. B.D. Lucas Generalized Image Matching by the Method of 'Differences. PhD thesis Carnegie Mellon Univ. July 1984.
30. B.D. Lucas and T. Kanade An Iterative Image Registration Technique with an Application in Stereo Vision Seventh Int'l Joint Conf. ArtifidallntelKgeMce (IJCAI-81) pp. 674-679 Vancouver 1981.
31. M.R. Luettgen W.C. Karl and A.S. Willsky Efficient Multiscale Rcgularization with Applications to the Computation of Optical Flow IEEE Trans. Image Processing vol. 3 no. 1 pp. 41-64 Jan. 1994.
32. S.G. Mallat A Theory for Multiresolution Signal Decomposition: The Wavelet Representation IEEE Trans. Pattern Analysis and Machine Intelligence vol. 11 no. 7 pp. 674-693 July 1989.
33. J. Marroquin S. Mittcr and T. Poggio Probabilistic Solution of Ill-Posed Problems in Computational Vision J. Am. Statistical Assoc. vol. 82 no. 397 pp. 76-89 Mar. 1987.
34. L.H. Matthies R. Szeliski and T. Kanade Kaiman Filter-Based Algorithms for Estimating Depth from Image Sequences Int'l ]. Computer Vision vol. 3 pp. 209-2361989.
35. J.R. Müller P. Anandan and J.R. Bergen Adaptive-Complexity Registration of Images IEEE CS Conf Computer Vision und Pattern Recognition (CVPR'94) pp. 953-957 Seattle Washington June 1994 lELh CSTress.
36. H.-H. Nagel On the Estimation of Optical Flow: Relations Between Different Approaches and Some New Results Artificial Intelligence vol. 33 pp. 299-3241987.
37. S. Negahdaripour and C.H. Yu A Generalized Brightness Change Model for Computing Optical Flow fourth Int'l Conf. Computer Vision CICCV'93) pp. 2-11 Berlin Germany May 1993 IEEE CS Press.
38. M. Okutomi and T. Kanade A Locally Adaptive Window fur Signal Matching Int'l f. Computer Vision vol. 7 no. 2 pp. 143-162 Apr. 1992.
39. M. Okutomi and T. Kanade A Multiple Baseline Stereo IEEE Trans. Pattern Analysis and Machine Intelligence vol. 15 no. 4 pp. 35.3-363 Apr. 1993.
40. M. Okutomi and T. Kanade A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment IEEE Trans. Pattern Analysis and Machine Intelligence vol. 16 no. 9 pp. 920-932 Sept. 1994.
41. M. Otte and H.-H. Nagel Optical Flow Estimation: Advances and Comparisons Third European Conf. Computer Vision (ECCV'94) vol. 1 pp. 51-60 Stockholm Sweden May 1994 Springer-Verlag.
42. A.P. Pentland Interpolation Using Wavelet Bases IEEE Trans. Pattern Analysis and Machine Intelligence vol. 16. no. 4 pp. 410-414 Apr. 1994
43. T. Poggio V. Torre and C. Koch Computational Vision and Regularization Theory Nature vol. 317 no. 6035 pp. 314-319 Sept. 261985.
44. [441 W.H. Press B.P. Flannery S.A. Teukolsky and W.T. Vetterling Numerical Recipes in C: The Art of Scientific Computing. Cambridge England: Cambridge Univ. Press 2nd ed. 1992.
45. L.H. Quam Hierarchical Warp Stereo Image Understanding Workshop pp. 149-155 New Orleans Louisiana Dec. 1984 Science Applications International Corporation.
46. J. Rehg and A. Witkin Visual Tracking with Deformation Models IEEE Int'l Conf. Robotics and Automation pp. 844-850 Sacramento California Apr. 1991 IEEE CS Press.
47. H. Samet The Design and Analysis of Spatial Date Structures. Reading Mass.: Addison-Wesley 1989.
48. J. Shi and C. Tomasi Good Features to Track IEEE CS Conf Computer Vision and Pattern Recognition (CVPR'94) pp. 593-600 Seattle Washington June 1994 IEEE CS Press.
49. T. Simchony R. Chellappa and Z. Lichtenstein Pyramid Implementation of Optimal-Step Conjugate-Search Algorithms for Some Low-Level Vision Problems IEEE Trans. Systems Man and Cybernetics vol. 19 no. 6 pp. 1408-1425 Nov./Dec. 1989.
50. EP. Simoncelli E.H. Adelson and DJ. Heeger Probability Distributions of Optic Flow IEEE CS Conf. Computer Vision and Pattern Recognition (CVPR'91) pp. 310-315 Maui Hawaii June 1991 IEEE CS Press.
51. A. Singh An Estimation-Theoretic Framework for Image-Flow Computation Third Int'l Corif. Computer Vision (ICCV90) pp. 168-177 Osaka Japan Dec. 1990 IEEE CS Press.
52. R. Szeliski Bayesian Modeling of Uncertainty in Low-Level Vision. Boston: Kluwer 1989.
53. R. Szeliski Fast Surface Interpolation Using Hierarchical Basis Functions IEEE Trans. Pattern Analysis and Machine Intelligence vol. 12 no. 6 pp. 513-528 June 1990.
54. R. Szeliski Fast Shape from Shading CVGIP: Image Understanding vol. 53 no. 2 pp. 129-153 Mar. 1991.
55. R. Szeliski and J. Coughlan Hierarchical Spline-Based linage Registration IEEE CS Conf. Computer Vision and Pattern Rfcognition (CVPR'94) pp. 194-201 Seattle Washington June 1994 IEEE CS Press.
56. R. Szeliski and J. Coughlan Hierarchical Spline-Based Image Registration Int'l]. Computer Vision to appear.
57. R. Szeliski S.B. Rang and H.-Y. Shum A Parallel Feature Tracker for Extended Image Sequences IEEE Int'l Symp. Computer Vision pp. 241-246 Coral Gables Florida Nov. 1995.
58. R. Szeliski and S.Lavallée Matching 3-D Anatomical Surfaces with Non-Rigid Deformations Using Octree-Splines Int'l J. Computer Vision vol. 18 no. 2 pp. 171-186 May 1996.
59. R. Szeliski and D. Terzopoulos Parallel Multigrid Algorithms and Computer Vision Applications Fourth Copper Mountain Conf. Multigrid Methods pp. 383-398 Copper Mountain Colorado Apr. 1989 Soc. for Industrial and Applied Math.
60. D. Terzopoulos Image Analysis Using Multigrid Relaxation Methods IEEE Trans. Pattern Analysis and Machine Intelligence vol. S no. 2 pp. 129-139 Mar. 1986.
61. C. Tomasi and T. Kanade Shape and Motion from Image Streams Under Orthography: A Factorization Method Int'l ]. Computer Vision vol. 9 no. 2 pp. 137-154 Nov. 1992.
62. J.Y.A. Wang and E.H. Adelson Layered Representation for Motion Analysis IEEE CS Conf. Computer Vision and Pattern Recognition (CVPR'93) pp. 361-366 New York June 1993.
63. J. Weber and J. Malik Robust Computation of Optical Flow in a MultiScale Differential Framework fourth Int'l Can]. Computer Vision (ICCV'93) pp. 12-20 Berlin Germany May 1993.. IEEE CS Press.
64. A. Witkin D. Terzopoulos and M. Kass Signal Matching Through Scale Space Int'l}. Computer Vision vol. 1 pp. 133-1441987.
65. H. Yserentant On the Multi-Level Splitting of Finite Element Spaces Numerische Mathematik vol. 49 pp. 379-4121986.