Evolving object detectors with a GPU accelerated vision system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6274 LNCS, Issue , 2010, Pages 109-120

  Ebner, Marc ^a  

^a UNIVERSITY OF TÜBINGEN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

GPU PROCESSING; INPUT IMAGE; INTERACTIVE FRAME RATES; LOW LEVEL; MATRIX; OBJECT DETECTION; OBJECT DETECTORS; RECOGNITION PERFORMANCE; SYSTEM USE; VISION SYSTEMS;

DETECTORS; IMAGING SYSTEMS;

OBJECT RECOGNITION;

EID: 78049367828     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15323-5_10     Document Type: Conference Paper

References (23)

1. Banzhaf, W., Nordin, P., Keller, R. E., Francone, F. D.: Genetic Programming - An Introduction: On The Automatic Evolution of Computer Programs and Its Applications. Morgan Kaufmann Publishers, San Francisco (1998)
2. Cagnoni, S.: Evolutionary computer vision: a taxonomic tutorial. In: 8th Int. Conf. on Hybrid Intelligent Systems, pp. 1-6. IEEE Comp. Soc., Los Alamitos (2008)
3. Ebner, M.: Engineering of computer vision algorithms using evolutionary algorithms. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds.) Advanced Concepts for Intelligent Vision Systems, Mercure Chateau Chartrons, Bordeaux, France, Berlin, pp. 367-378. Springer, Heidelberg (2009)
4. Ebner, M.: A real-time evolutionary object recognition system. In: Vanneschi, L., Gustafson, S., Moraglio, A., Falco, I. D., Ebner, M. (eds.) Genetic Programming: Proc. of the 12th Europ. Conf., Tübingen, Germany, pp. 268-279. Springer, Berlin (2009)
5. Ebner, M.: Towards automated learning of object detectors. In: Applications of Ev. Computation, Proc., Istanbul, Turkey, pp. 231-240. Springer, Berlin (2010)
6. Ebner, M., Zell, A.: Evolving a task specific image operator. In: Poli, R., Voigt, H.-M., Cagnoni, S., Corne, D., Smith, G. D., Fogarty, T. C. (eds.) Joint Proc. of the 1st Europ. Workshops on Evolutionary Image Analysis, Signal Processing and Telecommunications, Göteborg, Sweden, pp. 74-89. Springer, Berlin (1999)
7. Fung, J., Mann, S., Aimone, C.: OpenVIDIA: Parallel GPU computer vision. In: Int. Multimedia Conf. Proc. of the 13th annual ACM int. conf. on Multimedia, Singapore, vol. 5, pp. 849-852. ACM, New York (2005)
8. Fung, J., Tang, F., Mann, S.: Mediated reality using computer graphics hardware for computer vision. In: Proc. of the 6h Int. Symp. on Wearable Computers, pp. 83-89. ACM, New York (2002)
9. Harris, C., Buxton, B.: Evolving edge detectors with genetic programming. In: Koza, J. R., Goldberg, D. E., Fogel, D. B., Riolo, R. L. (eds.) Genetic Programming, Proc. of the 1st Annual Conf., Stanford University, pp. 309-314. The MIT Press, Cambridge (1996)
10. Jain, R., Kasturi, R., Schunck, B. G.: Machine Vision. McGraw-Hill, New York (1995)
11. Johnson, M. P., Maes, P., Darrell, T.: Evolving visual routines. In: Brooks, R. A., Maes, P. (eds.) Artificial Life IV, Proc. of the 4th Int. Workshop on the Synthesis and Simulation of Living Systems, pp. 198-209. The MIT Press, Cambridge (1994)
12. Katz, A. J., Thrift, P. R.: Generating image filters for target recognition by genetic learning. IEEE Trans. on Pattern Analysis and Machine Intelligence 16(9), 906-910 (1994)
13. Koza, J. R.: Genetic Programming. In: On the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge (1992)
14. Krawiec, K., Bhanu, B.: Visual learning by evolutionary and coevolutionary feature synthesis. IEEE Trans. on Evolutionary Computation 11(5), 635-650 (2007)
15. Lohmann, R.: Bionische Verfahren zur Entwicklung visueller Systeme. PhD thesis, Technische Universität Berlin, Verfahrenstechnik und Energietechnik (1991)
16. Miller, J. F.: An empirical study of the efficiency of learning boolean functions using a Cartesian Genetic Programming approach. In: Banzhaf, W., et al. (eds.) Proc. of the Genetic and Evolutionary Computation Conf., pp. 1135-1142. Morgan Kaufmann, San Francisco (1999)
17. NVIDIA. CUDA. Compute Unified Device Architecture. Version 1.1 (2007)
18. Poli, R.: Genetic programming for image analysis. In: Koza, J. R., Goldberg, D. E., Fogel, D. B., Riolo, R. L. (eds.) Proc. of the 1st Annual Conf. Genetic Programming, Stanford University, pp. 363-368. The MIT Press, Cambridge (1996)
19. Rizki, M. M., Tamburino, L. A., Zmuda, M. A.: Evolving multi-resolution featuredetectors. In: Fogel, D. B., Atmar, W. (eds.) Proc. of the 2nd Am. Conf. on Evolutionary Programming, pp. 108-118. Evolutionary Prog. Society (1993)
20. Rost, R. J.: OpenGL Shading Language, 2nd edn. Addison-Wesley, Upper Saddle River (2006)
21. Shapiro, L. G., Stockman, G. C.: Computer Vision. Prentice Hall, Upper Saddle River (2001)
22. Trujillo, L., Olague, G.: Synthesis of interest point detectors through genetic programming. In: Proc. of the Genetic and Evolutionary Computation Conf., Seattle, Washington, July 8-12, pp. 887-894. ACM, New York (2006)
23. Witkin, A. P.: Scale-space filtering. In: Proc. of the 8th Int. Joint Conf. on Artificial Intelligence, Karlsruhe, Germany, pp. 1019-1022 (1983)