A theory of shape identification

Lecture Notes in Mathematics

Volumn 1948, Issue , 2008, Pages 1-268

  Cao, Frédéric ^a   Lisani, José Luis ^b   Morel, Jean Michel ^c   Musé, Pablo ^d   Sur, Frédéric ^e  

^a DxO Labs   (France)

^b UNIVERSITAT DE LES ILLES BALEARS   (Spain)

^c UNIVERSITÉ PARIS SACLAY   (France)

^d Facultad de Ingenieria   (Uruguay)

^e LORIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 50549087954     PISSN: 00758434     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-68481-7     Document Type: Article

References (185)

1. Abbasi, S., Mokhtarian, F.: Retrieval of similar shapes under affine transformation. In: Proceedings of International Conference on Visual Information Systems, pp. 566-574. Amsterdam, The Netherlands (1999)
2. Almansa, A., Desolneux, A., Vamech, S.: Vanishing point detection without any a priori information. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(4), 502-507 (2003)
3. Alt, H., Guibas, L.: Discrete geometric shapes: Matching, interpolation, and approximation. In: J.R. Sack, J. Urrutia (eds.) Handbook of Computational Geometry, pp. 121-153. Elsevier Science Publishers (1999)
4. Alt, H., Knauer, C., Wenk, C.: Matching polygonal curves with respect to the Fréchet distance. In: Proceedings of the 18th International Symposium on Theoretical Aspects of Computer Science, pp. 63-74. Dresden, Germany (2001)
5. Alvarez, L., Guichard, F., Lions, PL., Morel, J.M.: Axioms and fundamental equations of image processing: Multiscale analysis and P.D.E. Archive for Rational Mechanics and Analysis 16(9), 200-257 (1993)
6. Alvarez, L., Mazorra, L., Santana, F.: Geometric invariant shape representations using morphological multiscale analysis and applications to shape representation. Journal of Mathematical Imaging and Vision 18(2), 145-168 (2002)
7. Angenent, S., Sapiro, G., Tannenbaum, A.: On the affine heat flow for nonconvex curves. Journal of the American Mathematical Society (1998)
8. Ansari, N., Delp, E.J.: Partial shape recognition: A landmark-based approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(5), 470-483 (1990)
9. Arnaud, N., Cavalier, F., Davier, M., Hello, P.: Detection of gravitational wave bursts by interferometric detectors. Physical review D 59(8), 082,002-1 - 082,002-9 (1999)
10. Asada, H., Brady, M.: The curvature primal sketch. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(1), 2-14 (1986)
11. Åström, K.: Affine and projective normalization of planar curves and regions. In: Proceedings of European Conference on Computer Vision, vol. 2, pp. 439-448. Stockholm, Sweden (1994)
12. Åström, K.: Fundamental, limitations on projective invariants of planar curves. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(1), 77-81 (1995)
13. Attneave, F.: Some informational aspects of visual perception. Psychological review 61(3), 183-193 (1954)
14. Ballard, D.: Generalizing the Hough transform, to detect arbitrary shapes. Pattern Recognition 13(2), 111-122 (1981)
15. Ballester, C., Caselles, V., Monasse, P.: The tree of shapes of an image. ESAIM.: Control, Optimisation and Calculus of Variations 9, 1-18 (2003)
16. Barles, G., Souganidis, P.: Convergence of approximation schemes for fully nonlinear second order equations. Asymptotic Analysis 4, 271-283 (1991)
17. Barlow, H.: What is the computational goal of the neocortex? Large-scale neuronal theories of the brain. MIT Press, Cambridge, MA (1994)
18. Basri, R., Costa, L., Geiger, D., Jacobs, D.: Determining the similarity of deformable shapes. Vision Research 38(15-16), 2365-2385 (1998)
19. Baumberg, A.: Reliable feature matching across widely separated views. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, pp. 774-781. Washington DC, USA (2004)
20. Beg, M.F., Miller, M., Trouvé, A., Younes, L.: Computing large deformation metric mappings via geodesic flows of diffeomorphisms. Internation Journal of Computer Vision 61(2), 139-157 (2005)
21. Belongie, S., Carson, C., Greenspan, H., Malik, J.: Color- and texture-based image segmentation using the Expectation-Maximization algorithm and its application to content-based image retrieval. In: Proceedings of the International Conference on Computer Vision, pp. 675-682. Mumbai, India (1998)
22. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(5), 509-522 (2002)
23. Bienenstock, E., Geman, S., Potter, D.: Compositionality, MDL priors, and object recognition. In: M. Mozera, M. Jordan, T. Petsche (eds.) Advances in Neural Information Processing Systems 9. MIT Press (1998)
24. Bock, H.: On some significance tests in cluster analysis. Journal of Classification 2, 77-108 (1985)
25. Bottou, L., Bengio, Y.: Convergence properties of the k-means algorithms. In: G. Tesario, D. Touretzky (eds.) Advances in Neural Information Processing Systems, vol. 7, pp. 585-592. Denver, Colorado, USA (1995)
26. Calinski, T., Harabasz, J.: A dendrite method for cluster analysis. Communications in statistics 3(1), 1-27 (1974)
27. Canny, J.: A variational approach to edge detection. In: National Conference on Artificial Intelligence, pp. 54-58. Washington DC, USA (1983)
28. Canny, J.: A. computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679-698 (1986)
29. Cao, F.: Geometric Curve Evolution and Image Processing, Lecture Notes in Mathematics, vol. 1805. Springer Verlag (2003)
30. Cao, F.: Good continuations in digital Images. In: Proceeding of International. Conference on Computer Vision, vol. 1, pp. 440-447. Nice, France (2003)
31. Cao, F.: Application of the Gestalt principles to the detection of good continuations and corners in image level lines. Computing and Visualisation in Science 7(1), 3-13 (2004)
32. Cao, F., Bouthemy, P.: A general criterion for image similarity detection. Technical Report IRISA 1732 (2005)
33. Cao, F., Delon, J., Desolneux, A., Musé, P., Sur, F.: A unified framework for detecting groups and application to shape recognition. Journal of Mathematical Imaging and Vision 27(2), 91-119 (2007)
34. Cao, F., Moisan, L.: A geometrical scheme for curve evolution driven by curvature. SIAM Journal, of Numerical. Analysis 39(2), 624-646 (2000)
35. Cao, F., Musé, P., Sur, F.: Extracting meaningful curves from images. Journal., of Mathematical Imaging and Vision 22(2-3), 159-181 (2005)
36. Caselles, V., Coll, B., Morel, J.M.: A Kanizsa program. Progress in Nonlinear Differential Equations and their Applications 25, 35-55 (1996)
37. Caselles, V., Coll, B., Morel, J.M.: Topographic maps and local contrast changes in natural images. International Journal of Computer Vision 33(1), 5-27 (1999)
38. Chappie, P., Bertilone, D., Caprari, R., Newsam, G.: Stochastic model-based processing for detection of small targets in non-gaussian natural imagery. IEEE Transactions on Image Processing 10(4), 554-564 (2001)
39. Cohen, F., Huang, Z., Yang, Z.: Invariant matching and identification of curves using B-Splines curve representation. IEEE Transactions on Image Processing 4(1), 1-10 (1995)
40. Cohignac, T.: Reconnaissance de formes planes. Ph.D. thesis, Ceremade, Université Paris IX Dauphine (1994)
41. Cohignac, T., Lopez, C., Morel, J.M.: Integral and local affine invariant parameter and application to shape recognition. In: International Conference on Pattern Recognition, pp. A: 164-168. Jerusalem, Israel (1994)
42. Cortadellas, J., Amat, J., de la Torre, F.: Robust normalization of silhouettes for recognition applications. Pattern Recognition Letters 25(5), 591-601 (2004)
43. Cox, J., Karron, D.: Digital Morse theory (1998). Manuscript available at http://www.casi.net/D.DMT/D.Overview/AcademicPressPaper 14-03
44. Day, W., Edelsbrunner, H.: Efficient algorithms for agglomerative hierarchical clustering methods. Journal of Classification 1(1), 7-24 (1984)
45. Debled-Rennesson, I., Rémy, J.L., Rouyer-Degli, J.: Segmentation of discrete curves into fuzzy segments. Tech. Rep. 4989, INRIA (2003)
46. Dempster, A., Laird, N., Rubin, D.: Maximum, likelihood from incomplete data via EM algorithm. Journal of the Royal Statistical Society, Series B 39, 1-38 (1977)
47. Deriche, R.: Using Canny's criteria to derive a recursively implemented optimal edge detector. International Journal of Computer Vision 1(2), 167-187 (1987)
48. Deriche, R., Faugeras, O.: Tracking line segments. Image and Vision Computing 8(4), 261-270(1990)
49. Desolneux, A., Ladjal, S., Moisan, L., Morel, J.M.: Dequantizing image orientation. IEEE Transactions on Image Processing 11(10), 1129-1140 (2002)
50. Desolneux, A., Moisan, L., Morel, J.M.: Meaningful alignments. International Journal of Computer Vision 40(1), 7-23 (2000)
51. Desolneux, A., Moisan, L., Morel, J.M.: Edge detection by Helmholtz principle. Journal of Mathematical Imaging and Vision 14(3), 271-284 (2001)
52. Desolneux, A., Moisan, L., Morel, J.M.: Computational gestalts and perception thresholds. Journal of Physiology - Paris 97(2-3), 311-322 (2003)
53. Desolneux, A., Moisan, L., Morel, J.M.: A grouping principle and four applications. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(4), 508-513 (2003)
54. Desolneux, A., Moisan, L., Morel, J.M.: Gestalt Theory and Image Analysis, a Probabilistic Approach. Interdisciplinary Applied Mathematics series, Springer Verlag (2007). Preprint available at http://www.cm.la.ens- cachan.fr/Utili.sateurs/morel/lecturenote.pdf
55. Devijver, P., Kittler, J.: Pattern recognition - A statistical approach. Prentice Hall (1982)
56. Donoser, M., Bischof, H.: Efficient Maximally Stable Extremal Region (MSER) Tracking. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Volume 1 pp. 553-560 (2006)
57. Dryden, I.: General shape and registration analysis. Tech. rep., University of Leeds, Department of Statistics (1996)
58. Dubes, R..C.: How many clusters are best? - an experiment. Pattern Recognition 20(6), 645-663 (1987)
59. Duda, R., Hart, P.: Pattern Classification and Scene Analysis. John Wiley and Sons (1973)
60. Duda, R., Hart, P., Stork, D.: Pattern Classification. John Wiley and Sons (2000). 2nd edition
61. Dudani, S., Breeding, K., McGhee, R.: Aircraft identification by moment invariants. IEEE Transactions on Computers 26(1), 39-46 (1977)
62. Dudek, G., Tsotsos, J.: Shape representation and recognition from multiscale curvature. Computer Vision and Image Understanding 2(68), 170-189 (1997)
63. Faugeras, O., Keriven, R.: Some recent results on the projective evolution of 2d curves. In: Proceedings of IEEE International Conference on Image Processing, vol. 3, pp. 13-16. Washington DC, USA (1995)
64. Fischler, M., Bolles, R.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the Association for Computing Machinery 24(6), 381-395 (1981)
65. Fischler, M., Bolles, R.: Perceptual organization and curve partitioning. IEEE Transactions on pattern analysis and machine intelligence 8(1), 100-105 (1986)
66. Frosini, P., Landi, C.: Size theory as a topological tool for computer vision. Pattern Recognition and Image Analysis 9(4), 596-603 (1999)
67. Frosini, P., Landi, C.: Size functions and formal series. Applicable Algebra in Engineering, Communication and Computing 12, 327-349 (2001)
68. Gdalyahu, Y., Weinshall, D.: Flexible syntactic matching of curves and its application to automatic hierarchical classification of silhouettes. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(12), 1312-1328 (1999)
69. Geman, S., McClure, D.: Statistical methods for tomographic image reconstruction. Bulletin of the International Statistical Institute 52, 5-21 (1987)
70. Giraudon, G.: Chaînage efficace de contour. Tech. Rep. 0605, INRIA (1987)
71. Golub, G., Loan, C.V.: Matrix Computations. Johns Hopkins University Press (1989)
72. Gordon, A.: Null models in cluster validation. In: W. Gaul, D. Pfeifer (eds.) From Data to Knowledge: Theoretical and Practical Aspects of Classification, Data Analysis, and Knowledge Organization, pp. 32-44. Springer Verlag (1996)
73. Gordon, A.: Classification. Monographs on Statistics and Applied Probability 82, Chapman & Hall (1999)
74. Gousseau, Y.: Comparaison de la composition de deux images, et. application à la recherche automatique. In: proceedings of GRETSI2003. Paris, France (2003)
75. Grimson, W., Huttenlocher, D.: On the sensitivity of the Hough transform for object .recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(3), 255-274 (1990)
76. Grimson, W., Huttenlocher, D.: On the verification of hypothesized matches in model-based recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 13(12), 1201-1213 (1991)
77. Guigues, L.: Modèles multi-échelles pour la segmentation d'images. Ph.D. thesis, Université de Cergy-Pontoise (2003)
78. Guy, G., Medioni, G.: Inferring global perceptual contours from local features. International Journal, on Computer Vision 20(1), 113-133 (1996)
79. Haralick, R.: Digital step edges from zero crossing of second directional derivatives. IEEE Transactions on Pattern Analysis and Machine Intelligence 6(1), 58-68 (1984)
80. Harris, C., Stephens, M.: A combined corner and edge detector. In: 4th Alvey Vision Conference, Manchester, pp. 189-192 (1988)
81. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press (2000)
82. Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning Data Mining, Inference, and Prediction. Springer Series in Statistics (2001)
83. Helmholtz, H.: Treatise on Physiological Optics. Dover, New York (1962 (first published in 1867))
84. Hoeffding, W.: Probability Inequalities for Sums of Bounded Random Variables. Journal of the American Statistical Association 58(301), 13-30 (1963)
85. Hough, P.: Methods and means for recognizing complex patterns (1962). U.S. Patent 3,069,654
86. Hu, M.: Visual, pattern recognition by moments invariants. IRE Transactions on Information Theory 8, 179-187(1962)
87. Huang, Z., Cohen, F.: Affine-invariant B-spline moments for curve matching. IEEE Transactions on Image Processing 5(10), 1473-1480 (1996)
88. Huttenlocher, D., Klanderman, G., Rucklidge, W.: Comparing images using the Hausdorff distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(9), 850-863 (1993)
89. Huttenlocher, D., Ullman, S.: Object recognition using alignment. In: International Conference of Computer Vision, pp. 267-291. London, UK (1987)
90. Hyvärinen, A.: Survey on independent component analysis. Neural Computing Surveys 2, 94-128 (1999)
91. lllingworth, J., Kittler, J.: A survey of the Hough transform. Computer Vision, Graphics, and Image Processing 44(1), 87-116 (1988)
92. Jacobs, D.: Robust and efficient detection of salient convex groups. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(1), 23-37 (1996)
93. Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering: a review. ACM. Computing Surveys 31(3), 264-323 (1999)
94. Joag-Dev, K., Proschan, F.: Negative association of random variables, with applications. Annals of Statistics 11(1), 286-295 (1983)
95. Kanizsa, G.: Organization in Vision: Essays on Gestalt Perception. Praeger (1979)
96. Kaufman, L., Rousseeuw, P.J.: Finding groups in data: an introduction to cluster analysis. John Wiley and Sons (1990)
97. Khalil, M., Bayoumi, M.: A dyadic wavelet affine invariant function for 2d shape recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10) (2001)
98. Koenderink, J.: The structure of images. Biological Cybernetics 50, 363-370 (1984)
99. Koepfler, G., Moisan, L.: Geometric multiscale representation of numerical images. In: Second International Conference on Scale Space Theories in Computer Vision, Lecture Notes in Computer Science, vol. 1682, pp. 339-350. Springer, Corfu, Greece (1999)
100. Krzyzak, A., Leung, S., Suen, C.: Reconstruction of two-dimensional patterns from Fourier descriptors. Machine Vision and Applications 2, 123-140 (1989)
101. Lamdan, Y., Schwartz, J., Wolfson, H.: Object recognition by affine invariant matching. In: Proceedings of IEEE International. Conference on Computer Vision and Pattern Recognition, pp. 335-344. Ann Arbor, Michigan, U.S.A. (1988)
102. Lamdan, Y., Wolfson, H.: Geometric hashing: a general and efficient model-based recognition scheme. In: Proceedings of IEEE International Conference on Computer Vision, pp. 238-249. Tampa, Florida, USA (1988)
103. Lance, G., Williams, W.: A. general theory of classificatory sorting strategies. I. hierarchical systems. Computer Journal. 9, 373-370 (1967)
104. Lin, C., Chellappa, R.: Classification of partial 2-d shapes using Fourier descriptors. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, pp. 344-350. Miami Beach, Florida, USA (1986)
105. Lindeberg, T.: Feature detection with automatic scale selection. International Journal of Computer Vision 30(2), 77-116 (1998)
106. Lindenbaum, M.: An integrated model for evaluating the amount of data required for reliable recognition. IEEE Trans. Pattern Analysis Machine Intelligence 19(11), 1251-1264 (1997)
107. Lindenbaum, M., Bruckstein, A.: On recursive, O(N) partitioning of a digitized curve into digital straight segments. Transactions on Pattern Analysis and Machine Intelligence 15(9) (1993)
108. Lisani, J.: Shape based automatic images comparison. Ph.D. thesis, Université Paris 9 Dauphine, France (2001)
109. Lisani, J., Moisan, L., Monasse, P., Morel, J.M.: On the theory of planar shape. SIAM Multiscale Modeling and Simulation 1(1), 1-24 (2003)
110. Lisani, J., Monasse, P., Rudin, L.: Fast shape extraction and applications. Tech. Rep. 2001-16, CMLA, ENS Cachan (2001)
111. Loncaric, S.: A survey of shape analysis techniques. Pattern Recognition 31(8), 983-1001 (1998)
112. Lowe, D.: Perceptual Organization and Visual Recognition. Kluwer Academic Publisher (1985)
113. Lowe, D.: Object recognition from local scale-invariant features. In: Proceedings of IEEE International Conference on Computer Vision, pp. 1150-1157. Corfu, Greece (1999)
114. Lowe, D.: Distinctive image features from scale-invariant key points. International Journal of Computer Vision 60(2), 9.1-110 (2004)
115. MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 63-74 (1967)
116. Marr, D.: Vision. Freeman Publishers (1982)
117. Marr, D., Hildreth, E.: Theory of edge detection. Proceeding of the Royal Society of London B-207, 187-207 (1980)
118. Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. Image and Vision Computing 22(10), 761-767 (2004)
119. Matheron, G.: Random Sets and Integral Geometry. John Wiley and Sons (1975)
120. Mikolajczyk, K., Schmid: A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(10), 1615-1630 (2005)
121. Mikolajczyk, K., Schmid, C.: Scale & affine invariant interest point detectors. International Journal of Computer Vision 60(1), 63-86 (2004)
122. Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Van Gool, L.: A comparison of affine region detectors. International Journal of Computer Vision 65(1-2), 43-72 (2005)
123. Miller, M., Trouvé, A., Younes, L.: On the metrics and Euler-Lagrange equations of computational anatomy. Annual Review of Biomedical Engineering 4, 375-405 (2002)
124. Miller, M.., Trouvé, A., Younes, L.: Geodesic shooting for computational anatomy. Journal of Mathematical Imaging and Vision 24(2), 209-228 (2006)
125. Milligan, G., Cooper, M.: An examination of procedures for determining the number of clusters in a data set. Psychometrika 50(2), 159-179 (1985)
126. Milnor, J.: Topology from the Differentiable Viewpoint. Princeton University Press (1997)
127. Moisan, L.: Affine plane curve evolution: A fully consistent scheme. IEEE Transactions on Image Processing 7(3), 411-420 (1998)
128. Moisan, L., Stival, B.: A probabilistic criterion to detect rigid point matches between two images and estimate the fundamental matrix. International Journal of Computer Vision 57(3), 201-218 (2004)
129. Mokhtarian, F.: Silhouette-based isolated object recognition through curvature scale space. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(5), 539-544 (1995)
130. Mokhtarian, F., Abbasi, S., Kittler, J.: Efficient and robust retrieval by shape content through curvature scale space. In: Proceedings of International Workshop on Image Databases and MultiMedia Search, pp. 35-42. Amsterdam, The Netherlands (1996)
131. Mokhtarian, F., Abbasi, S., Kittler, J.: Robust and efficient shape indexing through curvature scale space. In: Proceedings of British Machine Vision Conference, pp. 53-62. Edinburgh, UK (1996)
132. Mokhtarian, F., Mackworth, A.: A theory of multiscale, curvature-based shape representation for planar curves. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(8), 789-805 (1992)
133. Monasse, P.: Contrast invariant image registration. In: Proceedings of International Conference on Acoustics, Speech and Signal Processing, vol. 6, pp. 3221-3224. Phoenix, Arizona, USA (1999)
134. Monasse, P.: Représentation morphologique d'images numériques et application au recalage, morphological representation of digital images and application to registration. Ph.D. thesis, Université Paris 9 Dauphine, France (2000)
135. Monasse, P., Guichard, F.: Fast computation of a contrast invariant image representation IEEE Transactions on Image Processing 9(5), 860-872 (2000)
136. Monasse, P., Guichard, F.: Scale-space from a level, lines tree. Journal of Visual Communication and Image Representation 11, 224-236 (2000)
137. Morel, J.M., Solimini, S.: Variational Methods in Image Segmentation. Birkhauser (1995)
138. Murphy-Chutorian, E., Trivedi, M.: N-tree Disjoint-Set Forests for Maximally Stable Extremal Regions. In: Proceedings of the British Machine Vision Conference. Edinburgh, United Kingdom (2006)
139. Musé, P., Sur, F., Cao, F., Gousseau, Y.: Unsupervised thresholds for shape matching. In: Proceedings of IEEE International Conference on Image Processing. Barcelona, Spain (2003)
140. Musé, P., Sur, F., Cao, F., Gousseau, Y., Morel, J.M.: An A Contrario Decision Method for Shape Element Recognition. International Journal of Computer Vision 69(3), 295-315 (2006).
141. Musé, P., Sur, F., Morel, J.M.: Sur les seuils de reconnaissance des formes. Traitement du Signal 20(3), 279-294 (2003)
142. Niethammer, M., Betelu, S., Sapiro, G., Tannenbaum, A., Giblin, P.: Area-based medial axis of planar curves. International Journal of Computer Vision 60(3), 203-224 (2004)
143. Obdržálek, S., Matas, J.: Local affine frames for image retrieval. In: CIVR'02: Proceedings of International Conference The Challenge of Image and Video Retrieval, pp. 318-327. Springer-Verlag (2002)
144. Olson, C., Huttenlocher, D.: Automatic target recognition by matching oriented edge pixels. IEEE Transactions on Image Processing 6(12), 103-113 (1997)
145. Orrite, C., Herrero, J.: Shape matching of partially occluded curves invariant under projective transformation. Computer Vision and Image Understing 93(1), 34-64 (2004)
146. Papoulis, A., Bertran, M.: Digital filtering and prolate functions. IEEE Transactions on Circuits and Systems 19(6), 674-681 (1972)
147. Pennec, X.: Toward a generic framework for recognition based on uncertain geometric features. Videre: Journal of Computer Vision Research 1(2), 58-87 (1998)
148. Persoon, E., Fu, K.: Shape discrimination using Fourier descriptors. SMC 7(3), 170-179 (1977)
149. Poor, H.: An Introduction to Signal Detection and Estimation, 2nd edn. Springer Texts in Electrical Engineering. Springer Verlag (1994)
150. Rabin, J., Gousseau, Y., Delon, J.: A contrario matching of local descriptors. Tech. Rep. hal-00168285, Ecole Nationale Supérieure des Télécommunications, Paris, France (2007)
151. Rothwell, C.: Object Recognition Through Invariant Indexing. Oxford Science Publications (1995)
152. Rothwell, C., Zisserman, A., Forsyth, D., Mundy, J.: Planar object recognition using projective shape representation. International Journal of Computer Vision 16, 57-99 (1995)
153. Rubin, E.: Visuell wahrgenommene Figuren. Copenhagen, Gyldendals (1921)
154. Salembier, P., Serra, J.: Flat zones filtering, connected operators, and filters by reconstruction. IEEE Transactions on Image Processing 4(8), 1153-1160 (1995)
155. Sapiro, G., Tannenbaum, A.: Affine invariant scale-space. International Journal of Computer Vision 11(1), 25-44 (1993)
156. Sato, J., Cipolla, R.: Quasi-invariant parameterisations and matching of curves in images. International Journal of Computer Vision 28(2), 117-138 (1998)
157. Schmid, C., G., Dorko, Lazebnik, S., Mikolajczyk, K., Ponce., J.: Pattern recognition with local invariant features. In: C. Chen, e. P.S.P Wang (eds.) Handbook of Pattern Recognition and Computer Vision. World Scientific Publishing Co. (2005). 3rd edition
158. Schmid, C., Mohr, R.: Combining greyvalue invariants with local constraints for object recognition. In: Proc. CVPR96, pp. 872-877. San Francisco, California (1996)
159. Schmid, C., Mohr, R.: Local greyvalue invariants for image retrieval. IEEE Transaction on Pattern Analysis and Machine Intelligence 19(5), 530-535 (1997)
160. Sclaroff, S., Pentland, A.: Modal matching for correspondence and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(6), 545-561 (1995)
161. Serra, J.: Image Analysis and Mathematical Morphology. Academic Press (1982)
162. Shen, D., Ip, H.: Discriminative wavelet shape descriptors for recognition of 2-d patterns. Pattern Recognition 32(8), 151-165 (1999)
163. Sivic, J., Zisserman, A.: Video Google: a text retrieval approach to object matching in videos. In: Ninth IEEE International Conference on Computer Vision, pp. 1470-1477 (2003)
164. Sklansky, J., Gonzalez, V.: Fast polygonal approximation of digitized curves. Pattern Recognition 12, 327-331 (1980)
165. Small, C.: The Statistical Theory of Shapes. Springer Verlag (1996)
166. Song, Y.: A Top-down Algorithm for Computation of Level Line Trees. IEEE Transactions on Image Processing 16(8), 2107-2116 (2007)
167. Song, Y., Zhang, A.: Analyzing scenery images by monotonic tree. Multimedia Systems 8(6), 495-511 (2003)
168. Stewart, C.: MINPRAN: a new robust estimator for computer vision. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(10), 925-938 (1995)
169. Stockman, G., Kopstein, S., Benett, S.: Matching images to models for registration and object detection via clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 4(3), 229-241 (1982)
170. Tan, P., Steinbach, M., Kumar, V.: Introduction to Data Mining. Addison-Wesley (2005)
171. de la Torre, F., Black, M.: A framework, for robust subspace learning. International Journal of Computer Vision 54(1-2-3), 117-142 (2003)
172. Veltkamp, R.: Shape matching: similarity measures and algorithms. In: Proceedings of International Conference on Shape Modeling and Applications, pp. 188-197. Genova, Italy (2001)
173. Veltkamp, R., Hagedoorn, M.: State-of-the-art in shape matching. In: M. Lew (ed.) Principles of Visual Information Retrieval, vol. 19. Springer Verlag (2001)
174. Veltkamp, R., Tanase, M.: Content-based image retrieval systems: A survey. Tech. Rep. UU-CS-2000-34, Utrecht University (2000)
175. Venters, C.C., Cooper, M.D.: A review of content-based image retrieval systems. Tech. Rep. jtap-054, University of Manchester, UK (2000)
176. Ward, J.H.J.: Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 58(2), 236-244 (1963)
177. Watson, G., Watson, S.: Detection of unusual events in intermittent non-gaussian images using multiresolution background models. Optical Engineering 35(11), 3159-3171 (1996)
178. Weiss, I.: Noise-resistant invariants of curves. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(9), 943-948 (1993)
179. Wertheimer, M.: Untersuchungen zur Lehre der Gestalt, II. Psychologische Forschung 4, 301-350 (1923). Translation published as Laws of Organization in Perceptual. Forms, in Ellis, W. (1938). A source book of Gestalt psychology (pp. 71-88). Routledge & Kegan Paul
180. Winter, A., Nastar, C.: Differential feature distribution maps for image segmentation and region queries in image databases. In: CBAIVL Workshop at Conference on Computer Vision and Pattern Recognition. Fort Collins, Colorado, USA (1999)
181. Witkin, A.: Scale space filtering. In: Proceedings of International Joint Conference on Artificial Intelligence, pp. 1019-1021. Karlsruhe, Germany (1983)
182. Wolfson, H.: Model-based object recognition by Geometric Hashing. In: Proceedings of the European Conference on Computer Vision, pp. 526-536. Lecture Notes in Computer Vision 427, Springer Verlag, Antibes, France (1990)
183. Wolfson, H.: On curve matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(5), 483-489 (1990)
184. Wolfson, H., Rigoutsos, I.: Geometric hashing: an overview. IEEE Computational Science & Engineering 4(4), 10-21 (1997)
185. Zahn, C., Roskies, R.: Fourier descriptors for plane closed curves. IEEE Transactions on Computers C-21(3), 269-281 (1972)