Multiresolution estimates of classification complexity and multiple subspace classifiers for understanding and solving complex recognition tasks

Proceedings of the Third IASTED International Conference on Signal Processing, Pattern Recognition, and Applications

Volumn 2006, Issue , 2006, Pages 250-255

  Singh, Sameer ^a   Kumar, Varun ^a   Singh, Maneesha ^a  

^a LOUGHBOROUGH UNIVERSITY   (United Kingdom)

Author keywords

Classification complexity; Feature space partitioning; Subspace classifiers

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL COMPLEXITY; DATA REDUCTION; DATABASE SYSTEMS; PROBLEM SOLVING;

CLASSIFICATION COMPLEXITY; FEATURE SPACE PARTITIONING; SUBSPACE CLASSIFIERS;

PATTERN RECOGNITION;

EID: 33847231337     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (30)

1. A. Bhattacharya, "On a measure of divergence between two statistical populations defined by their probability distributions", Bulletin of Calcutta Maths Society, vol. 35, pp. 99-110, 1943.
2. C.H. Chen, "On information and distance measures, error bounds, and feature selection", Information Sciences, pp. 159-173, 1976.
3. A. Chernoff, "Estimation of a multivariate density", Annals of the Institute of Statistical Mathematics, vol. 18, pp. 179-189, 1966.
4. T.M. Cover and P.E. Hart, "Nearest neighbour pattern classification", IEEE Transactions on Information theory, pp. 21-27, 1967.
5. P.A. Devijver and J. Kittler, "Pattern recognition: a statistical approach", Prentice-Hall, New Jersey, 1982.
6. A. Fisher, The mathematical theory of probabilities, John Wiley, New York, 1923.
7. E. Fix and J.L. Hodges, "Discriminatory analysis, non-parametric discrimination: consistency properties", Technical report 21-49-004, USAF School of Aviation and Medicine, Randolph Air Field, TX , report no. 4, 1949.
8. nd edition, 1990.
9. T.K. Ho and H.S. Baird, "Estimating the intrinsic difficulty of a recognition problem", Proceedings of the 12th International Conference on Pattern Recognition, Jerusalem, Israel, 178-183, 1994.
10. T.K. Ho, "Complexity of classification problems and comparative advantages of combined classifiers", in Proc. First International Workshop on Multiple Classifier Systems, Lecture Notes in Computer science, no. 1857, pp. 97-106, 2000.
11. T.K. Ho and M. Basu, "Measuring the complexity of classification problems", Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, Spain, pp. 43-47, September 3-8, 2000.
12. T.K. Ho, "Data complexity analysis for classifier combination", Proceedings of the 2nd International Workshop on Multiple Classifier, Systems, Cambridge, U.K., July 2-4, 2001, 53-67.
13. T.K. Ho and M. Basu, "Complexity measures of supervised classification problems", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, issue 3, March 2002, 289-300.
14. J.K. Kishore, L.M. Patnaik, V. Mani and V.K. Agrawal, "Genetic programming based pattern classification with feature space partitioning", Information Sciences, vol. 131, pp. 65-86, 2001.
15. A. Kohn, L.G.M. Nakano and M.O. de Silvas, "A class discriminability measure based on feature space partitioning", Pattern Recognition, vol. 29, no. 5, pp. 873-887, 1996.
16. D.O. Loftsgaardne and C.P. Quesenberry, "A non-parametric estimate of multivariate density function", Annals of Mathematical Statistics, pp. 1049-1051, 1965.
17. E. Parzen, "On estimation of a probability density function and mode", Annals of Mathematical Statistics, vol. 33, pp. 1065-1076, 1962.
18. W.E. Pierson, "Using boundary methods for estimating class separability", PhD Thesis, Department of Electrical Engineering, Ohio State University, 1998.
19. W.E. Pierson, B. Ulug, S.C. Ahalt, J. L. Sancho and A. Figueiras-Vidal, "Theoretical and complexity issues for feature set evaluation using boundary methods", Proceedings of the SPIE Conference on Automatic target Recognition VII, ATR Theory and Performance Estimation, Orlando, 1998.
20. W. E. Pierson, B. Ulug, S. C. Ahalt, "On the use of boundary methods for measuring class separability", Submitted to: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002.
21. A.F.R. Rahman, M. Fairhurst, "Measuring classification complexity of image databases: a novel approach", Proceedings of International Conference on Image Analysis and Processing, pp. 893 -897, 1998.
22. J.L. Sancho, B. Ulug, A. Figueiras-Vidal, W. Pierson, and S.C. Ahalt, "Boundary methods for distribution analysis", in Intelligent Methods in Signal Processing and Communications, P.P. Gonzalez (ed), Birkhauser, Boston, MA, 1996a.
23. J. L. Sancho, A. R. Figueiras, B. Ulug, W. Pierson, and S. C. Ahalt, "Distribution analysis using boundary methods", Proceedings of the 1996 IEE Conference on Mathematics in Signal Processing, University of Warwick, England, 17-19 Dec. 1996b.
24. S. Singh "Multi-resolution estimates of classification complexity", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1534-1539, 2003.
25. S.Y. Sohn, "Meta analysis of classification algorithms for pattern recognition", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 11, pp. 1137-1144, 1999.
26. C.W. Therrien, Decision estimation and classification, John Wiley, 1989.
27. C.S. Wallace and D.M. Boulton, "An information theoretic measure for classification", Computer Journal, vol. 11, no. 2, pp. 185-194, 1968.
28. A.C. Williams, "A comparative study of the Gaussian form of the Bhattacharya metric for ATR performance evaluation", in SPIE International Symposium on Optical Engineering, 1997.
29. Q. Xie, C.A. Laszlo and R.K. Ward, "Vector quantization technique for non-parametric classifier design", IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1326-1330, 1993.
30. T.Y. Young and K.S. Fu, Handbook of Pattern Recognition and Image Processing, Academic Press, Orlando, Florida, 1986.