Stereo video surveillance multi-agent system: New solutions for human motion analysis

Journal of Mathematical Imaging and Vision

Volumn 42, Issue 2-3, 2012, Pages 176-195

  Pere, Marti Puig ^a   Rodríguez, Sara ^b   De Paz, Juan F ^b   Ramon, Reig Bolaño ^a   Rubio, Manuel P ^b   Bajo, Javier ^c  

^a UNIVERSITY OF VIC CENTRAL UNIVERSITY OF CATALONIA   (Spain)

^b UNIVERSITY OF SALAMANCA   (Spain)

^c UNIVERSIDAD PONTIFICIA DE SALAMANCA   (Spain)

Author keywords

Case based reasoning; Human detection; Multi agent systems; Stereo processing

Indexed keywords

AGENT-BASED SYSTEMS; CBR; DETECTION PROCESS; GLOBAL PROJECTS; HUMAN BEHAVIOR UNDERSTANDING; HUMAN DETECTION; HUMAN MOTION ANALYSIS; HUMAN TRACKING; INTELLIGENT ENVIRONMENT; MULTI AGENT SYSTEM (MAS); NEW SOLUTIONS; NOVEL TECHNIQUES; REAL TIME; REASONING CAPABILITIES; STEREO PROCESSING; STEREO VIDEO; STEREOSCOPIC CAMERA; STEREOSCOPIC IMAGE; TECHNIQUES USED; VISION ALGORITHMS; VISUAL INFORMATION;

CAMERAS; CASE BASED REASONING; MULTI AGENT SYSTEMS;

SECURITY SYSTEMS;

EID: 84863483154     PISSN: 09249907     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10851-011-0290-2     Document Type: Article

References (67)

1. Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7, 39-59 (1994)
2. Aggarwal, J.K., Cai, Q.: Human motion analysis: a review. Comput. Vis. Image Underst. 73(3), 428-440 (1999)
3. Aguilar, J.J., Torres, F., Lope,M.A.: Stereo vision for 3D measurement: accuracy analysis, calibration and industrial applications. Measurement 18(4), 193-200 (1996) (Pubitemid 126360253)
4. Aha, D., Kibler, D.: WInstance-based learning algorithms. Mach. Learn. 6, 37-66 (1991)
5. Alahi, A., Vandergheynst, P., Bierlaire, M., Kunt, M.: Cascade of descriptors to detect and track objects across any network of cameras. Comput. Vis. Image Underst. 114(6), 624-640 (2010)
6. Ardissono, L., Petrone, G., Segnan, M.: A conversational approach to the interaction with Web Services. Comput. Intell. 20, 693-709 (2004)
7. Bahadori, S., Cesta, A., Grisetti, G., Iocchi, L., Leonel, R., Nardi, D., Oddi, A., Pecora, F., Rasconi, R.: RoboCare: pervasive intelligence for the domestic care of the elderly. Intell. Artif. 1(1), 16-21 (2004)
8. Bahadori, S., Iocchi, L., Leone, G.R., Nardi, D., Scozzafava, L.: Real-time people localization and tracking through fixed stereo vision. In: Lecture Notes on Artificial Intelligence (LNAI), vol. 3533, pp. 44-54 (2005)
9. Bajo, J., de Paz, J.F., de Paz, Y., Corchado, J.M.: Integrating casebased planning and RPTW neural networks to construct an intelligent environment for health care. Expert Syst. Appl. 36(3), Part 2, 5844-5858 (2009)
10. Barron, J., Fleet, D., Beauchemin, S.: Performance of optical flow techniques. Int. J. Comput. Vis. 12(1), 42-77 (1994)
11. Breiman, L., Fried, J.H., Olshen, R.A., Stone, C.J.: Classification and regression trees. Wadsworth International Group (1984)
12. Brenner, W., Wittig, H., Zarnekow, R.: Intelligent Software Agents: Foundations and Applications. Springer, New York (1998)
13. Camarinha-Matos, L., Afsarmanesh, H.: Design of a virtual community infrastructure for elderly care. In: Proc. of 3rd IFIP Working Conference on Infrastructures for Virtual Enterprises: Collaborative Business Ecosystems and Virtual Enterprises, p. 635 (2002)
14. Camarinha-Matos, L.M., Afsarmanesh, H.: A comprehensive modeling framework for collaborative networked organizations. J. Intell. Manuf. 18(5), 529-542 (2007) (Pubitemid 47438603)
15. Castanedo, F., García, J., Patricio, M.A., Molina, J.M.: Designing a visual sensor network using a multi-agent architecture. In: Advances in Soft Computing, vol. 55, pp. 430-439 (2009). doi: 10.1007/978-3-642-00487-2-46
16. CIA: The World FactBook. ISSN 1553-8133 (2010)
17. Cohen, W.W.: Fast effective rule induction. In: Proceedings of the 12th International Conference on Machine Learning. Morgan Kaufmann, San Mateo (1995), pp. 115-123
18. Collins, R.T., Lipton, A.J., Kanade, T., Fujiyoshi, H., Duggins, D., Tsin, Y., Tolliver, D., Enomoto, N., Hasegawa, O., Burt, P., Wixson, L.: A system for video surveillance and monitoring. Tech. Rep., CMU-RI-TR-00-12. Carnegie Mellon Univ., Pittsburgh, PA (2000)
19. Comaniciu, D., Ramesh, V., Andmeer, P.: Kernel-based object tracking. IEEE Trans. Pattern Anal. Mach. Intell. 25, 564-575 (2003)
20. Corchado, J.M., Laza, R.: Constructing deliberative agents with case-based reasoning technology. Int. J. Intell. Syst. 18(12), 1227-1241 (2003)
21. Corchado, J.M., Bajo, J., De Paz, Y., Tapia, D.I.: Intelligent Environment for Monitoring Alzheimer Patients, Agent Technology for Health Care. Decision Support Systems. Elsevier, Amsterdam (2006)
22. Corchado, J.M., Glez-Bedia, M., de Paz, Y., Bajo, J., de Paz, J.F.: Concept, formulation and mechanism for agent replanification: MRP architecture. In: Computational Intelligence. Blackwell Publishers, Malden (2008)
23. Corchado, J.M., Glez-Bedia, M., de Paz, Y., Bajo, J., de Paz, J.F.: Replanning mechanism for deliberative agents in dynamic changing environments. Comput. Intell. 24(2), 77-107 (2008) (Pubitemid 351733114)
24. Cucchiara, R., Grana, C., Piccardi,M.: Prati, A. Detecting moving objects, ghosts, and shadows in video streams. IEEE Trans. Pattern Anal. Mach. Intell. 25(10), 1337-1342 (2003)
25. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Conference Computer Vision and Pattern Recognition, USA, pp. 886-893 (2005) (Pubitemid 43897286)
26. Davies, E.R.: Lateral histograms for efficient object location: speed versus ambiguity. Pattern Recognit. Lett. 6(3), 189-198 (1987)
27. Dietterich, T.G.: Approximate statistical tests for comparing supervised classification learning algorithms. Neural Computation 1895-1923 (1998) (Pubitemid 128463689)
28. Duda, R.O., Hart, P.: Pattern Classification and Scene Analysis. Wiley, New York (1973)
29. Eddy, S.R.: HiddenMarkov models. Curr. Opin. Struct. Biol. 6(3), 361-365 (1996)
30. Elgammal, H.M., Harwood, D., Davis, L.S.: Non-parametric model for background subtraction. In: Proc. of the 6th European Conference on Computer (ECCV). Springer, London (2000), pp. 751-767
31. Freund, Y., Schapire, R.E.: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning (1996), pp. 148-156
32. Gallagher, M., Downs, T.: Visualization of learning in multilayer perceptron networks using principal component analysis. IEEE Trans. Syst. Man Cybern., Part B, Cybern. 33, 28-34 (2003)
33. Garvey, A.J., Lesser, V.R.: Design-to-time real-time scheduling. IEEE Trans. Syst. Man Cybern.. 23, 1491-1502 (1993)
34. Gu, Z., Su, X., Liu, Y., Zhang, Q.: Local stereo matching with adaptive support-weight, rank transform and disparity calibration. Pattern Recognit. Lett. 29(9), 1230-1235 (2008)
35. Haritaoglu, I., Harwood, D., Davis, L.S.: W4: real-time surveillance of people and their activities. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 809-830 (2000)
36. Ivanciuc, O.: Applications of support vector machines in chemistry. In: Lipkowitz, K.B., Cundari, T.R. (eds.) Reviews in Computational Chemistry, vol. 23, pp. 291-400.Wiley, New York (2007)
37. Jabri, S., Duric, Z., Wechsler, H., Rosenfeld, A.: Detection and location of people in video images using adaptive fusion of color and edge information. In: Proc. of 15th International Conference on Pattern Recognition (ICPR'00), vol. 4, p. 4627 (2000)
38. Jeong, Y.-S., Jeong, M.K., Omitaomu, O.A.: Weighted dynamic time warping for time series classification. Pattern Recogn. (2011). doi: 10.1016/j.patcog.2010.09.022
39. Kim, K., Chalidabhongse, T.H., Harwood, D. Davis, L.: Real-time foreground-background segmentation using codebook model. Real-Time Imaging 11(3), 172-185 (2005) (Pubitemid 40929458)
40. Kohlrausch, J., Rohr, K., Stiehl, H.S.: A new class of elastic body splines for nonrigid registration of medical images. J.Math. Imaging Vis. 23(3), 253-280 (2005). doi: 10.1007/s10851-005-0483-7 (Pubitemid 41312630)
41. Lima, C.A.M., Coelho, A.L.V., Von Zuben, F.J.: Hybridizing mixtures of experts with support vector machines: investigation into nonlinear dynamic systems identification. Inf. Sci. 177, 2049-2074 (2007) (Pubitemid 46371297)
42. Lindeberg, T.: Feature detection with automatic scale selection. Int. J. Comput. Vis. 30, 77-116 (1998)
43. Moeslund, T.B., Granum, E.: A survey of computer vision based human motion capture. Comput. Vis. Image Underst. 81(3), 231-268 (2001) (Pubitemid 32415976)
44. Moeslund, T.B., Hilton, A., Kruger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2), 90-126 (2007)
45. Mughadam, B., Pentland, A.: Probabilistic visual learning for object representation. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 696-710 (1997) (Pubitemid 127762262)
46. Murray, D., Little, J.J.: Using real-time stereo vision for mobile robot navigation. Auton. Robots 8(2), 161-171 (2000). doi: 10.1023/A: 1008987612352 (Pubitemid 30594909)
47. Nguyena, M.H., Abbassa, H.A., Mckay, R.I.: A novel mixture of experts model based on cooperative coevolution. Neurocomputing 70, 155-163 (2006)
48. Paragios, N., Deriche, R.: Geodesic active regions and level set methods for supervised texture segmentation. Int. J. Comput. Vis. 46(3), 223-247 (2002) (Pubitemid 34265799)
49. Platt, J.C.: Fast training of support vector machines using sequential minimal optimization. In: Advances in Kernel Methods, pp. 185-208 (1999)
50. Platt, J.C.: Fast training of support vector machines using sequential minimal optimization, pp. 185-208 (1999)
51. Point Grey Research Inc.: http://www.ptgrey.com/ (2009)
52. Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo (1993)
53. Rangarajan, A., Hsiao, I.-T., Gindi, G.: A Bayesian joint mixture framework for the integration of anatomical information in functional image reconstruction. J. Math. Imaging Vis. 12(3), 199-217 (2000). doi: 10.1023/A: 1008314015446
54. Rao, A.S., Georgeff, M.P.: BDI agents: from theory to practice. In: Proceedings of ICMAS'95. San Francisco, CA, USA (1995)
55. Rodríguez, S., De Paz, J.F., Bajo, J., Tapia, D.I., Pérez, B.: Stereo-MAS: multi-agent system for image stereo processing. In: Cabestany, J., et al. (eds.) IWANN'09. LNAI, vol. 5517, pp. 1256-1263. Springer, Berlin (2009). ISBN: 978-3-540-87655-7
56. Sato, K., Aggarwal, J.: Temporal spatio-velocity transform and its application to tracking and interaction. Comput. Vis. Image Underst. 96(2), 100-128 (2004)
57. Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, London (1982)
58. Stauffer, C., Grimson, W.E.L.: Learning patterns of activity using real-time tracking. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 747-757 (2000)
59. Subasi, A.: EEG signal classification using wavelet feature extraction and a mixture of expert model. Expert Syst. Appl. 32, 1084-1093 (2007) (Pubitemid 44821797)
60. Vapnik, V., Lerner, A.: Pattern recognition using generalized portrait method, pp. 774-780 (1963)
61. Veenman, C., Reinders, M., Backer, E.: Resolving motion correspondence for densely moving points. IEEE Trans. Pattern Anal. Mach. Intell. 23(1), 54-72 (2001) (Pubitemid 32168406)
62. Wang, L., Hu, W., Tan, T.: Recent development in human motion analysis. Pattern Recognit. 36(3), 585-601 (2003)
63. Wren, C.R., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: Real-time tracking of the human body. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 780-785 (1997) (Pubitemid 127762271)
64. Yilmaz, A., Li, X., Shah, M.: Contour based object tracking with occlusion handling in video acquired using mobile cameras. IEEE Trans. Pattern Anal. Mach. Intell. 26(11), 1531-1536 (2004) (Pubitemid 40168029)
65. Yilmaz, A., et al.: Object tracking: a survey. ACM J. Comput. Surv. 38(4) (2006)
66. Zhanga, H., Lu, J.: Creating ensembles of classifiers via fuzzy clustering and deflection. 161(13), 1790-1802 (2010)
67. Zitnick, C.L., Kang, S.B.: Stereo for image-based rendering using image over-segmentation. Int. J. Comput. Vis. 75(1), 49-65 (2007) (Pubitemid 47120245)