Overview of Object Detection and Image Analysis by Means of Genetic Programming Techniques
Inhaltsverzeichnis
Reference
Krzysztof Krawiec and Daniel Howard and Mengjie Zhang: Overview of Object Detection and Image Analysis by Means of Genetic Programming Techniques. Proceedings of the 2007 International Conference Frontiers in the Convergence of Bioscience and Information Technologies (FBIT 2007), pp. 779-784, IEEE Press, October 11-13 2007.
DOI
http://dx.doi.org/10.1109/FBIT.2007.148
Abstract
This paper reviews the existing work in genetic programming for object detection and image analysis. It shortly introduces the reader into the fundamentals of evolutionary computation and presents the basics of the genetic programming paradigm (GP), providing a rationale for the use of GP within computer vision and pattern recognition, particularly when applied to object detection and image analysis. It reviews the past research on GP for vision, referring to real-world applications where possible. It outlines possible further research directions.
Extended Abstract
Bibtex
Used References
D. Ashlock. GP-automata for dividing the dollar. In J. R. Koza, K. Deb, M. Dorigo, D. B. Fogel, M. Garzon, H. Iba, and R. L. Riolo, editors, Genetic Programming 1997: Proceedings of the Second Annual Conference, pages 18-26, Stanford University, CA, USA, 13-16 July 1997. Morgan Kaufmann.
J. H. Avila. The feasibility of continuation methods for nonlinear equations. SIAM J. Numer. Anal., 11(1): 153-171, March 1974.
W. Banzhaf, P. Nordin, R. Keller, and F. Francone. Genetic Programming: An Introduction. On the automatic Evolution of Computer Programs and its Application. Morgan Kaufmann, 1998.
J. M. Daida, T. F. Bersano-Begey, S. J. Ross, and J. F. Vesecky. Computer-assisted design of image classification algorithms: Dynamic and static fitness evaluations in a scaffolded genetic programming environment. In J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, editors, Genetic Programming 1996: Proceedings of the First Annual Conference, pages 279-284, Stanford University, CA, USA, 28-31 July 1996. MIT Press.
C. Fogelberg and M. Zhang. Linear genetic programming for multi-class object classification. In S. Zhang and R. Jarvis, editors, AI 2005: Advances in Artificial Intelligence, 18th Australian Joint Conference on Artificial Intelligence, Proceedings, volume 3809 of Lecture Notes in Computer Science, pages 369-379, Sydney, Australia, Dec. 5-9 2005. Springer.
D. Goldberg. Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading, 1989.
D. E. Goldberg. Genetic algorithms and walsh functions: part ii, deception and its analysis. Complex Systems, (3): 153-171, 1989.
D. Howard. Modularization by multi-run frequency driven subtree encapsulation. In R. L. Riolo and B. Worzel, editors, Genetic Programming Theory and Practise, chapter 10, pages 155-172. Kluwer, 2003.
D. Howard and S. C. Roberts. A staged genetic programming strategy for image analysis. In W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, editors, Proceedings of the Genetic and Evolutionary Computation Conference, volume 2, pages 1047-1052, Orlando, Florida, USA, 13-17 July 1999. Morgan Kaufmann.
D. Howard and S. C. Roberts. Genetic programming solution of the convection-diffusion equation. In L. Spector, E. D. Goodman, A. Wu, W. B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. H. Garzon, and E. Burke, editors, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), pages 34-41, San Francisco, California, USA, 7-11 July 2001. Morgan Kaufmann.
D. Howard and S. C. Roberts. The prediction of journey times on motorways using genetic programming. In S. Cagnoni, J. Gottlieb, E. Hart, M. Middendorf, and G. Raidl, editors, Applications of Evolutionary Computing, Proceedings of EvoWorkshops2002: EvoCOP, EvoIASP, EvoSTim/EvoPLAN, volume 2279 of LNCS, pages 210-221, Kinsale, Ireland, 3-4 Apr. 2002. Springer-Verlag.
D. Howard, S. C. Roberts, and R. Brankin. Evolution of ship detectors for satellite SAR imagery. In R. Poli, P. Nordin, W. B. Langdon, and T. C. Fogarty, editors, Genetic Programming, Proceedings of EuroGP'99, volume 1598 of LNCS, pages 135-148, Goteborg, Sweden, 26-27 May 1999. Springer-Verlag.
D. Howard, S. C. Roberts, and C. Ryan. Pragmatic genetic programming strategy for the problem of vehicle detection in airborne reconnaissance. Pattern Recognition Letters, 27(11): 1275-1288, Aug. 2006. Evolutionary Computer Vision and Image Understanding.
M. Johnson. Evolving visual routines. Master's thesis, Massachusetts Institute of Technology, 1995.
M. Keijzer. Improving symbolic regression with interval arithmetic and linear scaling. In C. Ryan, T. Soule, M. Keijzer, E. Tsang, R. Poli, and E. Costa, editors, Genetic Programming, Proceedings of EuroGP'2003, volume 2610 of LNCS, pages 70-82, Essex, 14-16 Apr. 2003. Springer-Verlag.
M. Keijzer, C. Ryan, G. Murphy, and M. Cattolico. Undirected training of run transferable libraries. In M. Keijzer, A. Tettamanzi, P. Collet, J. I. van Hemert, and M. Tomassini, editors, Proceedings of the 8th European Conference on Genetic Programming, volume 3447 of Lecture Notes in Computer Science, pages 361-370, Lausanne, Switzerland, 30 Mar. -1 Apr. 2005. Springer.
J. Koza. Genetic Programming. MIT Press, Cambridge, MA, 1992.
J. Koza. Genetic programming - 2. MIT Press, Cambridge, MA, 1994.
J. Koza. Human-competitive applications of genetic programming. In A. Ghosh and S. Tsutsui, editors, Advances in Evolutionary Computing, pages 663-682. Springer-Verlag, 2003.
K. Krawiec. Pairwise comparison of hypotheses in evolutionary learning. In C. Brodley and A. Pohoreckyj-Danyluk, editors, Proc. Eighteenth International Conference on Machine Learning, pages 266-273, San Francisco, 2001. Morgan Kaufmann.
K. Krawiec. Learning high-level visual concepts using attributed primitives and genetic programming. In F. R., editor, EvoWorkshops 2006, LNCS 3907, pages 515-519, Berlin Heidelberg, 2006. Springer-Verlag.
K. Krawiec and B. Bhanu. Visual learning by revolutionary feature synthesis. IEEE Transactions on System, Man, and Cybernetics - Part B, 35(3):409-425, June 2005.
M. Lett and M. Zhang. New fitness functions in genetic programming for object detection. In D. Pairman, H. North, and S. McNeill, editors, Proceeding of Image and Vision Computing International Conference, pages 441-446, Akaroa, New Zealand, Nov. 2004. Lincoln, Landcare Research.
Z. Michalewicz. Genetic algorithms + data structures = evolution programs. Springer-Verlag, Berlin, 1994.
R. Poli. Genetic programming for image analysis. In J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, editors, Genetic Programming 1996: Proceedings of the First Annual Conference, pages 363-368, Stanford University, CA, USA, 28-31 July 1996. MIT Press.
R. Poli. Exact schema theory for genetic programming and variable-length genetic algorithms with one-point crossover. Genetic Programming and Evolvable Machines, 2(2):123-163, June 2001.
M. Rizki, M. A. Zmuda, and L. A. Tamburino. Evolving pattern recognition systems. IEEE Transactions on Evolutionary Computation, 6(6):594-609, 2002. http://dx.doi.org/10.1109/TEVC.2002.806167
S. C. Roberts and D. Howard. Evolution of vehicle detectors for infrared linescan imagery. In R. Poli, H.-M. Voigt, S. Cagnoni, D. Corne, G. D. Smith, and T. C. Fogarty, editors, Evolutionary Image Analysis, Signal Processing and Telecommunications: First European Workshop, EvoIASP'99 and EuroEcTel'99, volume 1596 of LNCS, pages 110-125, Goteborg, Sweden, 28-29 May 1999. Springer-Verlag.
S. C. Roberts and D. Howard. Genetic programming for image analysis: Orientation detection. In D. Whitley, D. Goldberg, E. Cantu-Paz, L. Spector, I. Parmee, and H.-G. Beyer, editors, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000), pages 651-657, Las Vegas, Nevada, USA, 10-12 July 2000. Morgan Kaufmann.
S. C. Roberts, D. Howard, and J. R. Koza. Evolving modules in genetic programming by subtree encapsulation. In M. Tomassini, C. Ryan, A. G. B. Tettamanzi, and W. B. Langdon, editors, Genetic Programming, Proceedings of EuroGP'2001, volume 2038 of LNCS, pages 160-175, Lake Como, Italy, 18-20 Apr. 2001. Springer-Verlag.
C. Ryan. Pygmies and civil servants. In K. E. Kinnear, Jr., editor, Advances in Genetic Programming, chapter 11, pages 243-263. MIT Press, 1994.
C. Ryan, M. Keijzer, and M. Cattolico. Favorable biasing of function sets using run transferable libraries. In U.-M. O'Reilly, T. Yu, R. L. Riolo, and B. Worzel, editors, Genetic Programming Theory and Practice II, chapter 7, pages 103-120. Springer, Ann Arbor, 13-15 May 2004.
C. Ryan and M. Nicolau. Doing genetic algorithms the genetic programming way. In R. L. Riolo and B. Worzel, editors, Genetic Programming Theory and Practice, chapter 12, pages 189-204. Kluwer, 2003.
W. A. Tackett. Genetic programming for feature discovery and image discrimination. In S. Forrest, editor, Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-93, pages 303-309, University of Illinois at UrbanaChampaign, 17-21 July 1993. Morgan Kaufmann.
A. Teller and M. Veloso. PADO: A new learning architecture for object recognition. In K. Ikeuchi and M. Veloso, editors, Symbolic Visual Learning, pages 77-112. Oxford Press, New York, 1997.
L. Trujillo and G. Olague. Synthesis of interest point detectors through genetic programming. In M. Keijzer, M. Cattolico, D. Arnold, V. Babovic, C. Blum, P. Bosman, M. V. Butz, C. Coello Coello, D. Dasgupta, S. G. Ficici, J. Foster, A. Hemandez-Aguirre, G. Hornby, H. Lipson, P. McMinn, J. Moore, G. Raidl, F. Rothlauf, C. Ryan, and D. Thierens, editors, GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, volume 1, pages 887-894, Seattle, Washington, USA, 8-12 July 2006. ACM Press.
S.Ullman. Visual routines. Cognition, 18:97-159, 1984. http://dx.doi.org/10.1016/0010-0277(84)90023-4
J. F. Winkeler and B. S. Manjunath. Genetic programming for object detection. In J. R. Koza, K. Deb, M. Dorigo, D. B. Fogel, M. Garzon, H. Iba, and R. L. Riolo, editors, Genetic Programming 1997: Proceedings of the Second Annual Conference, pages 330-335, Stanford University, CA, USA, 13-16 July 1997. Morgan Kaufmann.
M. Zhang, V. B. Ciesielski, and P. Andreae. A domainindependent window approach to multiclass object detection using genetic programming. EURASIP Journal on Applied Signal Processing, 2003(8):841-859, July 2003. Special Issue on Genetic and Evolutionary Computation for Signal Processing and Image Analysis. http://dx.doi.org/10.1155/S1110865703303063
Links
Full Text
[extern file]
