An Adaptive On-Line Evolutionary Visual System
Marc Ebner: An Adaptive On-Line Evolutionary Visual System. Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW 2008, pp. 84-89, IEEE Press, 20-24 October 2008.
In evolutionary computer vision, algorithms are usually evolved which address one particular computer vision problem. Quite often, a set of training images is used to evolve an algorithm. Another set of images is then used to evaluate the performance of those algorithms. In contrast of this standard form of algorithm evolution, it is proposed to develop a vision system which continuously evolves algorithms based on the task at hand. This adaptation of computer vision algorithms would happen on-line for every image which is presented to the system. Such a system would continuously adapt to new environmental conditions.
M. Ebner, "Aktuelles schlagwort: Evolutionare bildverar-beitung, " Informatik-Spektrum, vol. 31, no. 2, pp. 146-150, Apr. 2008. http://dx.doi.org/10.1007/s00287-008-0230-8
J. H. Holland, Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. Cambridge, Massachusetts: The MIT Press, 1992.
R. Jain, R. Kasturi, and B. G. Schunck, Machine Vision.New York: McGraw-Hill, Inc., 1995.
L. G. Shapiro and G. C. Stockman, Computer Vision.New Jersey: Prentice Hall, 2001.
R. Lohmann, "Selforganization by evolution strategy in visual systems," in Evolution and Optimization '89, H.-M. Voigt, H. Muhlenbein, and Hans-Paul-Schwefel, Eds. Akademie-Verlag, 1990, pp. 61-68. http://dx.doi.org/10.1007/3-540-55027-5_29
"Bionische Verfahren zur Entwicklung visueller Systeme," Ph.D. dissertation, Technische Universitat Berlin, Fachbereich 10 Verfahrenstechnik und Energietechnik, 1991.
M. Ebner, "On the evolution of edge detectors for robot vision using genetic programming," in Workshop SOAVE '97-Selbstorganisation von Adaptivem Verhalten, VDI Reihe 8 Nr. 663, H.-M. GroB, Ed.Dusseldorf: VDI Verlag, 1997, pp. 127-134.
"Evolution of hierarchical translation-invariant feature detectors with an application to character recognition," in Mustererkennung 1997, 19. DAGM-Symposium Braunschweig, 15.-17. September 1997,E.Paulusand F. M. Wahl, Eds. Berlin: Springer-Verlag, 1997, pp. 456-463.
"On the evolution of interest operators using genetic programming," in Late Breaking Papers at EuroGP'98: the First European Workshop on Genetic Programming, Riccardo Poli, W. B. Langdon, Marc Schoenauer, Terry Fogarty, and Wolfgang Banzhaf, Eds. Paris, France: The University of Birmingham, UK, 14-15 Apr. 1998, pp. 6-10.
M. Ebner and A. Zell, "Evolving a task specific image operator," in Joint Proceedings of the First European Workshops on Evolutionary Image Analysis, Signal Processing and Telecommunications(EvoIASP'99 and EuroEcTel'99), Göteborg, Sweden, 1999, R. Poli, H.-M. Voigt, S. Cagnoni, D. Corne, G. D. Smith, and T. C. Fogarty, Eds. Berlin: Springer-Verlag, May 1999, pp. 74-89.
R. Poli, "Genetic programming for image analysis," in Genetic Programming 1996, Proceedings ofthe First Annual Conference, July 28-31, 1996, Stanford University,J.R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, Eds. Cambridge, Massachusetts: The MIT Press, 1996, pp. 363-368.
M. P. Johnson, P. Maes, and T. Darrell, "Evolving visual routines," in Artificial Life IV, Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems, R. A. Brooks and P. Maes, Eds. Cambridge, Massachusetts: The MIT Press, 1994, pp. 198-209. http://dx.doi.org/10.1109/ICPR.1996.546164
L. Trujillo and G. Olague, "Synthesis of interest point detectors through genetic programming," in Proceedings ofthe Genetic and Evolutionary Computation Conference 2006, Seattle, Washington, July 8-12. ACM, 2006, pp. 887-894. http://dx.doi.org/10.1145/1143997.1144151
A. Treptow and A. Zell, "Combining adaboost learning and evolutionary search to select features for real-time object detection," in Proceedings ofthe IEEE Congress on Evolutionary Computation, Portland, Oregon, vol. 2. IEEE, 2004, pp. 2107-2113.
P. Heinemann, F. Streichert, F. Sehnke, and A. Zell, "Automatic calibration of camera to world mapping in robocup using evolutionary algorithms," in Proceedings ofthe IEEE International Congress on Evolutionary Computation, San Francisco, CA. IEEE, 2006, pp. 1316-1323. http://dx.doi.org/10.1109/CEC.2006.1688461
M. Mitchell, An Introduction to Genetic Algorithms.Cam-bridge, Massachusetts: The MIT Press, 1996.
I. Rechenberg, Evolutionsstrategie '94. Stuttgart: frommann-holzboog, 1994.
J. R. Koza, Genetic Programming. On the Programming of Computers by Means of Natural Selection. Cambridge, Massachusetts: The MIT Press, 1992.
W. Banzhaf, P. Nordin, R. E. Keller, and F. D. Francone, Genetic Programming-An Introduction: On The Automatic Evolution ofComputer Programs and Its Applications.San Francisco, California: Morgan Kaufmann Publishers, 1998.
J. R. Koza, "Artificial life: Spontaneous emergence of self-replicating and evolutionary self-improving computer programs," in Artificial Life III: SFI Studies in the Sciences of Complexity Proc. Vol. XVII, C. G. Langton, Ed. Reading, Massachusetts: Addison-Wesley, 1994, pp. 225-262.
P. Nordin, "A compiling genetic programming system that directly manipulates the machine code," in Advances in Genetic Programming,K.E.Kinnear,Jr.,Ed. Cambridge, Massachusetts: The MIT Press, 1994, pp. 311-331.
J. F. Miller, "An empirical study of the efficiency of learning boolean functions using a cartesian genetic programming approach," in Proceedings ofthe Genetic and Evolutionary Computation Conference, W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, Eds. San Francisco, California: Morgan Kaufmann, 1999, pp. 1135-1142.
J. D. Owens, D. Luebke, N. Govindaraju, M. Harris, J. Kriiger, A. E. Lefohn, and T. J. Purcell, "A survey of general-purpose computation on graphics hardware," in Eurographics 2005, State of the Art Reports, Aug. 2005, pp. 21-51. http://dx.doi.org/10.1111/j.1467-8659.2007.01012.x
I. Buck, T. Foley, D. Horn, J. Sugerman, K. Fatahalian, M. Houston, and P. Hanrahan, "Brook for gpus: Stream computing on graphics hardware," in International Conference on Computer Graphics and Interactive Techniques(ACM SIGGRAPH), Aug. 2004, pp. 777-786.
NVIDIA, NVIDIA CUDA. Compute Unified Device Architecture. Version 1.1, 2007.
J. Fung, F. Tang, and S. Mann, "Mediated reality using computer graphics hardware for computer vision," in Proceedings ofthe Sixth International Symposium on Wearable Computers ACM, 2002, pp. 83-89. http://dx.doi.org/10.1109/ISWC.2002.1167222
R. Yang and M. Pollefeys, "Multi-resolution real-time stereo on commodity graphics hardware," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2003, pp. 211-218.
J. Fung and S. Mann, "Computer vision signal processing on graphics processing units," in Proceedings ofthe IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004, vol. 5. IEEE, 2004, pp. 93-96.
J. Fung, S. Mann, and C. Aimone, "Openvidia: Parallel gpu computer vision," in International Multimedia Conference. Proceedings of the 13th annual ACM international conference on Multimedia, Singapore, vol. 5. ACM, 2005, pp. 849-852.
T. Akenine-Moller and E. Haines, Real-Time Rendering, 2nd ed. Natick, Massachusetts: A K Peters, 2002.
OpenGL Architecture Review Board, D. Shreiner, M. Woo, J. Neider, and T. Davis, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Version 2, 5th ed. Reading, Massachusetts: Addison-Wesley, 2006.
R. Fernando and M. J. Kilgard, The Cg Tutorial. The Definitive Guide to Programmable Real-Time Graphics. Boston, Massachusetts: Addison-Wesley, 2003.
R. J. Rost, OpenGL Shading Language. With contributions by John M. Kessenich, Barthold Lichtenbelt, Hugh Malan, and Mike Weiblen, 2nd ed.Upper Saddle River, NJ: Addison-Wesley, 2006.