Inter-image outliers and their application to image classification

Pattern Recognition

Volumn 43, Issue 12, 2010, Pages 4101-4112

  Pappachen James, Alex ^a,b   Dimitrijev, Sima ^a  

^a GRIFFITH UNIVERSITY   (Australia)

^b GRIFFITH UNIVERSITY   (Australia)

Author keywords

Image recognition; Outliers; Template matching

Indexed keywords

FACE IMAGES; ILLUMINATION VARIATION; IMAGE PIXELS; OUTLIERS; POSE VARIATION; RECOGNITION METHODS; RECOGNITION PERFORMANCE; SIMILARITY CALCULATION;

DATABASE SYSTEMS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; PIXELS; TEMPLATE MATCHING;

FACE RECOGNITION;

EID: 77957017440     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2010.07.005     Document Type: Article

References (75)

1. V. Barnett, and T. Lewis Outliers in Statistical Data 1994 John Wiley and Sons
2. D. Hawkins Identification of Outliers 1980 Chapman and Hall
3. C.-T. Lu, D. Chen, Y. Kou, Algorithms for spatial outlier detection, in: Third IEEE International Conference on Data Mining, p. 597.
4. V.P. Jeneja, and V. Atluri Spatial outlier detection in heterogeneous neighborhoods Intelligent Data Analysis 13 2009 85 107
5. Z.-Q. Wang, S.-K. Wang, T. Hong, X.-H. Wan, A spatial outlier detection algorithm based multi-attributive correlation, in: Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004, pp. 17271732.
6. S. Shekhar, C.-T. Lu, P. Zhang, S. Shekhar, C.T. Lu, and P. Zhang A unified approach to spatial outliers detection GeoInformatica 7 2003 139 166
7. S. Chawla, and P. Sun Slom a new measure for local spatial outliers Knowledge and Information Systems 9 2006 412 429
8. Y. Kou, C.T. Lu, R.F. DosSantos, Spatial outlier detection: a graph-based approach, in: Proceedings of the 19th International Conference on Tools with Artificial Intelligence, 2007, pp. 281288.
9. S. Shekhar, C.-T. Lu, P. Zhang, Detecting graph-based spatial outliers: algorithms and applications (a summary of results), in: Proceedings of the seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2001, pp. 371376.
10. M. Agyemang, K. Barker, and R. Alhajj A comprehensive survey of numeric and symbolic outlier mining techniques Intelligent Data Analysis 10 2006 521 538
11. M.E. abd, H.-P. Kriegel, J. Sander, and X. Xu A density-based algorithm for discovering clusters in large spatial databases with noise E. Simondis, J. Han, U. Fayyad, Proceedings of the KDD 1996 AAAI Press Menlo Park, CA 226 231
12. R. Ng, J. Han, Efficient and effective clustering methods for spatial data mining, in: Proceedings of VLDB, Morgan Kaufmann, San Francisco, 1994, pp. 144155.
13. T. Zhang, R. Ramakrishnan, and M. Livay Brich: an efficient data clustering method for very large databases Proceedings of ACM SIGMOD 1996 ACM New York 103 114
14. E.M. Knorr, R.T. Ng, and V. Tucakov Distance-based outliers: algorithms and applications The VLDB JournalThe International Journal on Very Large Data Bases 8 2000 237 253
15. E.M. Knorr, R.T. Ng, Algorithms for mining distance-based outliers in large datasets, in: Proceedings of the 24rd International Conference on Very Large Data Bases, 1998, pp. 392403.
16. M. Agyemang, K. Barker, and R. Alhajj A comprehensive survey of numeric and symbolic outlier mining techniques Intelligent Data Analysis 10 2006 521 538
17. F. Angiulli, and F. Fassetti Dolphin: an efficient algorithm for mining distance-based outliers in very large datasets ACM Transactions on Knowledge Discovery from Data (TKDD) 3 2009 1 57
18. R. Brunelli Template Matching Techniques in Computer Vision: Theory and Practice 2009 Wiley
19. R.J. Baron Mechanisms of human facial recognition International Journal of Man Machine Studies 15 1981 137 178
20. D.H. Ballard Generalizing the hough transform to detect arbitrary shapes Pattern Recognition 13 1981 111 122
21. R.O. Duda, and P.E. Hart Use of hough transforms to detect lines and curves in picture ACM Communications 15 1972 11 15
22. R.T. Chin, and C.R. Dyer Model-based recognition in robot vision ACM Computing Surveys 18 1986 67 108
23. W.E.L. Grimson Object Recognition by Computer: The Role of Geometric Constraints 1990 MIT Press Cambridge, MA
24. P.E. Anuta Digital image registration of multi-spectral video imagery Society of Photo-Optical Instrumentation Engineers Journal 7 1969 168 175
25. D.I. Barnea, and H.F. Silverman A class of algorithms for fast digital image registration IEEE Transactions on Computers C-21 1972 179 186
26. M. Svedlow, C.D. McGillem, P.E. Anuta, Experimental examination of similarity measures and processing methods used for image registration, in: Symposium on Machine Processing Remotely Sensed Data, 1976.
27. D.V.S. Chandra, W.W.M.J.S. Boland, H.S. Ranganth, Feature matching multiple image registration using haar coefficients, in: SOUTHCON, 1982, pp. 549552.
28. H. Schutte, S. Frydrychowicz, J. Scnroder, Scene matching with translation invariant transforms, in: 5th International Joint Conference on Pattern Recognition, 1980, pp. 195198.
29. R.Y. Wong, and E.L. Hall Scene matching with invariant moments Computer Graphics and Image Processing 8 1978 16 24
30. M.-K. Hu Visual pattern recognition by moment invariants Transactions on Information Theory 1962 179 187
31. A. Goshtasby Template matching in rotated images IEEE Transactions on Pattern Analysis and Machine Intelligence 7 1985 338 344
32. B. Widrow The rubber mask technique, parts i and ii Pattern Recognition 5 1973 175 211
33. M. Fichler, and R. Elschlager The representation and matching of pictorial structures IEEE Transactions on Computers 22 1973 67 92
34. M. Kass, A. Witkin, and D. Terzopoulous Snakes: active contour models International Journal on Computer Vision 1 1988 321 331
35. R. Malladi, J. Sethain, and B. Vemuri Shape modelling with front propagation: a level set approach IEEE Transaction on Pattern Analysis and Machine Intelligence 17 1995 158 175
36. L. Cohen Note on active contour models and balloons CVGIP: Image Understanding 53 1991 211 218
37. L.H. Staib, and J.S. Duncan Boundary finding with parametrically deformable models IEEE Transaction on Pattern Analysis and Machine Intelligence 14 1992 1061 1075
38. A.L. Yuille, P.W. Hallinan, and D.S. Cohen Feature extraction from faces using deformable templates International Journal of Computer Vision 8 1992 133 144
39. Y. Zhong, Object matching using deformable templates, Ph.D. Thesis, Michigan State University, 1997.
40. L.C. Jain, U. Halici, I. Hayashi, S. Lee, S. Tsutsui (Eds.), Intelligent Biometric Techniques in Fingerprint and Face Recognition, Crc Press International Series on Computational Intelligence, CRC, 1999.
41. G. Guo Face, Expression, and Iris Recognition Using Learning-Based Approaches 2008 VDM Verlag
42. K. Delac, and M. Grgic Face Recognition 2007 I-Tech Education and Publishing Vienna, Austria
43. H. Wechsler Reliable Face Recognition Methods 2006 Springer Berlin/Heidelberg
44. W. Zhao, and R. Chellappa Face Processing: Advanced Modeling and Methods 2005 Academic Press
45. S.Z. Li, and A.K. Jain Handbook of Face Recognition 2005 Springer Berlin/Heidelberg
46. M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. von der Malsburg, R. Wurtz, and W. Konen Distortion invariant object recognition in the dynamic link architecture IEEE Transactions on Computers 42 1993 300 311
47. H. Chen, P. Belhumeur, and D. Jacobs In search of illumination invariants IEEE Proceedings on Computer Vision and Pattern Recognition 1 2000 254 261
48. D. Jacobs, P. Belhumeur, and R. Basri Comparing images under variable illumination IEEE Proceedings on Computer Vision and Pattern Recognition 1998 610 617
49. P. Belhumeur, J. Hespanha, and D. Kriegman Eigenfaces vs. fisherfaces: recognition using class specific linear projection IEEE Transactions on Pattern Analysis and Machine Intelligence 19 1997 711 720
50. Y. Adini, Y. Moses, and S. Ullman Face recognition: the problem of compensating for changes in illumination direction IEEE Transactions on Pattern Analysis and Machine Intelligence 19 1997 721 732
51. H. Chen, P. Belhumeur, and D. Jacobs In search of illumination invariants IEEE Proceedings on Computer Vision and Pattern Recognition 2000 254 261
52. Y. Moses, S. Ullman, Limitations of non model-based recognition schemes, in: European Conference on Computer Vision, 1991, pp. 820828.
53. A.M. Martinez Recognizing imprecisely localized, partially occluded and expression variant faces from a single sample per class IEEE Transactions on Pattern Analysis and Machine Intelligence 24 2002
54. D. Beymer, T. Poggio, Face recognition from one example view, in: Proceedings of the 5th International Conference on Computer Vision, Boston, MA, USA, 1995, pp. 500507.
55. V. Blanz, and T. Vetter Face recognition based on fitting a 3d morphable model IEEE Transactions on Pattern Analysis and Machine Intelligence 25 2003 1063 1074
56. D. Jiang, Y. Hu, S. Yan, L. Zhang, H. Zhang, and W. Gao Efficient 3d reconstruction for face recognition Pattern Recognition 38 2005 787 798
57. H. Ling, S. Soatto, N. Ramanathan, D. Jacobs, A study of face recognition as people age, in: IEEE International Conference on Computer Vision (ICCV), 2007, pp. 18.
58. N. Ramanathan, R. Chellappa, Face verification across age progression, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, 2005, pp. 462469.
59. N. Ramanathan, R. Chellappa, Modeling age progression in young faces, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, 2006, pp. 387394.
60. A.M. Martinez, R. Benavente, The ar face database, CVC Technical Report 24, 1998.
61. A.M. Martinez, R. Benavente, Ar face database, 2000. Available from http://rvl.www.ecn.purdue.edu/RVL/database.htm .
62. W.L. Martinez, and A.R. Martinez Exploratory Data Analysis with MATLAB 2004 Chapman and Hall
63. P.W. Hallinan, G. Gordon, A.L. Yuille, P. Giblin, and D. Mumford Two- and Three-Dimensional Patterns of the Face 1999 AK Peters, Ltd
64. A. Kasinski, A. Florek, and A. Schmidt The put face database Image Processing and Communications 13 2008 59 64
65. A. Georghiades, P. Belhumeur, and D. Kriegman From few to many: illumination cone models for face recognition under variable lighting and pose IEEE Transactions on Pattern Analysis and Machine Intelligence 23 2001 643 660
66. W.-C. Kao, M.-C. Hsua, and Y.-Y. Yang Local contrast enhancement and adaptive feature extraction for illumination-invariant face recognition Pattern Recognition 43 2010 1736 1747
67. A.S. Tolba, A. El-Baz, and A. El-Harby Face recognition: a literature review International Journal of Signal Processing 2 2006 88 103
68. W. Zhao, R. Chellappa, A. Rosenfeld, and P.J. Phillips Face recognition: a literature survey ACM Computing Surveys 2003 399 458
69. M. Turk, and A. Pentland Eigenfaces for recognition Journal of Cognitive Neuroscience 3 1991 71 86
70. H. Yu, and J. Yan A direct lda algorithm for high-dimensional data with application to face recognition Pattern Recognition 34 2001 2067 2070
71. O. Deniz, M. Castrillon, and M. Hernandez Face recognition using independent component analysis and support vector machines Pattern Recognition Letters 24 2003 2153 2157
72. Y. Gao, and K. Leung Face recognition using line edge map IEEE Transactions on Pattern Analysis and Machine Intelligence 24 2002
73. J. Huang, P. Yuen, W. Chen, and J. Lai Choosing parameters of kernel subspace lda for recognition of face images under pose and illumination variations IEEE Transactions on Systems Man Cybernetics B 37 2007 847 862
74. P. Belhumeur, J. Hespanha, and D. Kriegman Eigenfaces vs. fisherfaces: recognition using class specific linear projection IEEE Transactions on Pattern Analysis and Machine Intelligence 9 1997 711 720
75. J.R.M.M.S. Bartlett, and T.J. Sejnowski Face recognition by independent component analysis IEEE Transactions on Neural Network 13 2002 1450 1464