Video tracking system optimization using evolution strategies

International Journal of Imaging Systems and Technology

Volumn 17, Issue 2, 2007, Pages 75-90

  García, Jesús ^a   Pérez, Oscar ^a   Berlanga, Antonio ^a   Molina, José M ^a  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

Author keywords

Learning; Optimization; Surveillance systems; Tracking; Video

Indexed keywords

AIRPORTS; ALGORITHMS; OPTIMIZATION; TRAJECTORIES; VISION;

EVOLUTION STRATEGIES (ES); GENERALIZATION CAPABILITY; VIDEO TRACKING SYSTEMS;

TRACKING (POSITION);

EID: 34548269512     PISSN: 08999457     EISSN: 10981098     Source Type: Journal    
DOI: 10.1002/ima.20100     Document Type: Article

References (46)

1. B. Abidi, A. Koschan, S. Kang, M. Mitckes, and M. Abidi, "Automatic target acquisition and tracking with cooperative fixed and PTZ video cameras," In C.S. Regazzoni, P.K. Varshney, G.L. Foresti, Ed., Multisensor surveillance systems: The fusion perspective, Kluwer Academic Publishers, Boston, MA, June 2003, pp. 43-59.
2. ASMGCS, European Manual of Advanced Surface Movement and Control Systems (ASMGCS), Draft, Vol. 1: Operational requirements, Version 04. 08/24/2000.
3. T. Bäck, Evolutionary algorithms in theory and practice, Oxford University Press, New York, 1996.
4. T. Bäck, D.B. Fogel, and Z. Michalewicz, Evolutionary computation: Advanced algorithms and operators, Institute of Physics, London, 2000a.
5. T. Bäck, D.B. Fogel, and Z. Michalewicz, Evolutionary computation: Basic algorithms and operators, Institute of Physics, London, 2000b.
6. J.A. Besada, J. Portillo, J. García, J.M. Molina, Á. Varona, and G. Gonzalez, Image-based automatic surveillance for airport surface, FUSION 2001 Conf, Montreal, Canada, August 2001a.
7. J. Black, T. Ellis, and P. Rosin, Multi view image surveillance and tracking, IEEE Workshop on Motion and Video Computing, Orlando, December 2002, pp. 169-174.
8. S. Blackman and R. Popoli, Design and analysis of modern tracking systems, Artech House, 1999.
9. S.A. Branko Ristic and N. Gordon, Beyond the kalman filter: Particle filters for tracking applications, Artech House, 2004.
10. R. Castaldo, C.C. Franck, and A. Smith, Evaluation of FLIR/IR camera technology for airport surface surveillance, In SPIE 10th Annual Int AeroSense Symp, Orlando, FL, April 1996.
11. Y.L. Chang and J.K. Aggawal, 3D structure reconstruction from an ego motion sequence using statistical estimation and detection theory, Proc IEEE Workshop on Visual Motion, 1991, pp. 268-273.
12. T.P. Chen, H. Haussecker, A. Bovyrin, R. Belenov, K. Rodyushkin, A. Kuranov, and V. Eruhimov, Computer vision workload analysis: Case study of video surveillance systems, Intel Technol J 9 (2005), 109-118.
13. I. Cohen and G. Medioni, Detecting and tracking moving objects in video from an airborne observer, Proc IEEE Image Understanding Workshop, 1998, pp. 217-222.
14. D. Comaniciu and P. Meer, Mean shift analysis and applications, Computer Vision, 1999, The Proceedings of the Seventh IEEE International Conference on Computer Vision, Vol. 2, 1999, pp. 1197-1203.
15. D. Comaniciu, V. Ramesh, and P. Meer, Real-time tracking of non-rigid objects using mean shift, IEEE International Conference on Pattern Recognition, Vol. 2, 13-15 June, 2000, pp. 142-149.
16. I.J. Cox and S.L. Hingorani, An efficient implementation of reid's multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking. IEEE Trans Pattern Anal Mach Intell 18 (1996), 138-150.
17. F. Cupertino, E. Mininno, and D. Naso, Elitist compact genetic algorithms for induction motor self-tuning control, 2006 IEEE Congress on Evolutionary Computation, Sheraton Vancouver Wall Centre Hotel, Vancouver, BC, Canada, 16-21 July, 2006.
18. F. Cupillard, F. Bremond, and M. Thonnat, Tracking groups of people for video surveillance, Video-based surveillance systems, Computer vision and distributed processing, Kluwer Academic, 2002.
19. X. Desurmont, A. Bastide, J. Cqz, C Parisot, J.-F. Delaigle, and B. Macq, "A general-purpose system for distributed surveillance and communication". In S. Velastin, P. Remagnino, Ed., Intelligent distributed video surveillance systems, Institution of Engineering and Technology, Feb 2006. ISBN: 978-0863415043.
20. D. Doermann and D. Mihalcik, Tools and techniques for video performance evaluation, Proc Int Conf Pattern Recognit (IPCER'00), Barcelona, September 2000, pp. 4167-4170.
21. FAA, U.S. Department of Transportation, The future airport surface movement safety, guidance and control systems: A vision for transition into the 21st Century, U.S. Department of Transportation, Washington, November 1993.
22. G.L. Foresti, C Micheloni, L. Snidaro, P. Remagnino, and T. Ellis, Active video-based surveillance system: The low-level image and video processing techniques needed for implementation, IEEE Signal Proc Mag 22 (2005), 25-37.
23. D.A. Forsyth, Computer vision: A modern approach, Prentice Hall, 2003.
24. L.M. Fuentes and S.A. Velastin, Assessment of image processing techniques as a means of improving personal security in public transport, Video-based surveillance systems, Computer vision and distributed processing, Kluwer Academic, 2002.
25. J. García, J.A. Besada, A. Berlanga, J.M. Molina, G. de Miguel, and J.R. Casar, Application of evolution strategies to the design of tracking filters with a large number of specifications, EURASIP J Appl Signal Process (Special Issue on Genetic and Evolutionary Computation for Signal Processing and Image Analysis) 8 (2003), 766-779.
26. J. García, J.M. Molina, J.A. Besada, J. Portillo, A multitarget tracking video system based on fuzzy and neuro-fuzzy techniques, EUROASIP Journal on Applied Signal Processing 14 (2005), 2341-2358.
27. M. Isard and A. Blake, Condensation: Conditional density propagation for visual tracking, Int J Comput Vis 29 (1998), 5-28.
28. D. Koller, G. Klinker, E. Rose, D. Breen, R. Whitaker, M. Tuceryan. Real-time vision-based camera tracking for augmented reality applications, In ACM Symp on Virtual Reality Software and Technology, 1997.
29. Y. Kuno, Detecting and tracking people in complex scenes, Saitama University. Video-based surveillance systems, Computer vision and distributed processing, Kluwer Academic, 2002.
30. L. Li, W. Huang, I.Y.H. Gu, and Q. Tian, Statistical modeling of complex backgrounds for foreground object detection, IEEE Trans Image Process 13 (2004), 1459-1472.
31. B.D. Lucas and T. Kanade, An iterative image registration technique with an application to stereo vision, Proc. 7th Int'l Joint Conf. on Artificial Intelligence, 1981, pp. 674-679.
32. A. Mittal and L.S. Davis, M2Tracker: A multi-view approach to segmenting and tracking people in a cluttered scene, Int J Comput Vis 51 (2003), 189-203.
33. K. Nummiaro, E. Kollm-Meier, and L. VanGool, An adaptive color-based particle filter. Image Vis Comput 21 (2003), 99-110.
34. M.A. Patricio, J. Carbó, O. Pérez, J. García, and J.M. Molina, Multi-agent framework in visual sensor networks, EURASIP J Appl Signal Process (Special issue on Visual Sensor Networks) 2007, 21. Article ID 98639.
35. I. Rechenberg, Evolutionsstrategie'94, FrommannHolzboog, Stuttgart, 1994.
36. P.L. Rosin, Thresholding for change detection, Comput Vis Image Understand 86 (2002), 79-95.
37. P.L. Rosin and E. Ioannidis, Evaluation of global image thresholding for change detection, Pattern Recognit Lett 24 (2003), 2345-2356.
38. H.-P. Schwefel, Numerische Optimierung von computer-modellen mittels der evolutionsstrategie, Birkḧauser, Basel, 1977.
39. H.-P. Schwefel, Evolution and optimum seeking: The sixth generation,Wiley, New York, NY, 1995.
40. D.D. Silva Pires, R.M. Cesar Jr., M.B. Vieira, and L. Velho, Tracking and matching connected components from 3D video, Sibgrapi, 2005, 257-264.
41. L. Snidaro and G.L. Foresti, A multi-camera approach to sensor evaluation in video surveillance, Proc Int Conf Image Process, Genoa, Italy, Vol. 1, 11-14 September, 2005, pp. 1101-1104.
42. B.W. Wah, Generalization and generalizability measures, IEEE Trans Knowledge Data Eng 11 (1999), 175-186.
43. B. Zhang, W. Tian, and Z. Jin, Joint tracking algorithm using particle filter and mean shift with target model updating, Chin Opt Lett 4 (2006), 569-572.
44. Y. Zhong, A.K. Jain, and M.P. Dubiuson-Jolly, Object tracking using deformable templates, IEEE Trans Pattern Anal Mach Intell 22 (2000), 544-549.
45. S. Zhou, R Chellappa, and B. Moghaddam, Visual tracking and recognition using appearance-adaptive models in particle filters. IEEE Trans Image Process (TIP) 11 (2004), 1434-1456.
46. F. Ziliani and A. Cavallaro, Image analysis for video surveillance based on spatial regularization of a statistical model-based change detection, Real-Time Imaging 7 (2001), 389-399.