RAF: A dynamic and efficient approach to fusion for multitarget tracking in CCTV surveillance

IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems

Volumn 2003-January, Issue , 2003, Pages 269-274

  Hsu, D F ^a   Lyons, D M ^a   Usandivaras, C ^a   Montero, F ^a  

^a FORDHAM UNIVERSITY   (United States)

Author keywords

Bayesian methods; Cameras; Color; Data mining; Layout; Merging; Scalability; Surveillance; Target tracking; Video sequences

Indexed keywords

BAYESIAN NETWORKS; CAMERAS; COLOR; DATA MINING; INTELLIGENT SYSTEMS; MERGING; MONITORING; SCALABILITY; SECURITY SYSTEMS; SPACE SURVEILLANCE;

BAYESIAN METHODS; CCTV SURVEILLANCE; LAYOUT; LOW COMPUTATIONAL COMPLEXITY; MULTI-TARGET TRACKING; MULTIPLE FEATURES; SENSORY INFORMATION; VIDEO SEQUENCES;

TARGET TRACKING;

EID: 84943560812     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MFI-2003.2003.1232669     Document Type: Conference Paper

References (20)

1. Reid, D.B., An Algorithm for Tracking Multiple Targets. IEEE Trans. on Aut. Control, 1979. AC-24(6): p. 843-854.
2. Bar-Shalom, Y., Fortmann, T.,, Tracking and Data Association. 1988: Academic Press.
3. Cox, I.J., Hingorani, S.L. An Efficient Implementation and Evaluation of Reid's Multiple Hypothesis Tracking Algorithm for Visual Tracking. in Int. Conf. on Pattern Recognition. 1994.
4. Rasmussen, C., Hager, G.,. Joint Probabalistic Techniques for tracking Multi-Part Objects. in Proc. Computer Vision & Pattern Recognition. 1998. Santa Barbara CA.
5. Varshney, P.K., Special Issue on Data Fusion. Proceedings of the IEEE, 1997. 85(1).
6. Loy, G., Fletcher, L., Apostoloff, N., Zelinsky, A. An Adaptive Fusion Architecture for Target Tracking. in Proceedings of the 5th Int. Conf. on Face and Gesture Recog. 2002. Washington DC.
7. Rao, B., Data Association Methods for Tracking Systems, in Active Vision, A. Blake, Yuille, A.,, Editor. 1992, MIT Press, p. 91-106.
8. Cox, I.J., Miller, M.L., On Finding Ranked Assignments with Application to Multi-Target Tracking and Motion Correspondence. IEEE Trans. AES, 1995. 32(1): p. 486-489.
9. Liggins II, M.E., Kadar, I., Vannicola, V., Distributed Fusion Architectures and Algorithms for Target Tracking. Proc. of the IEEE, 1997. 85(1): p. 95-107.
10. Vogt, C.C., Cotrell, G.W., Fusion via a linear combination of scores. Information Retrieval, 1999. 1(3): p. 151-172.
11. Ng, K.B., Kantor, P.B., Predicting the effectiveness of Niave Data Fusion on the basis of system characteristics. Jour. American Soc. Info. Sc., 2000. 51(13): p. 1177-1189.
12. Hsu, D.F., Shapiro, J., Taksa, I., Methods of Data Fusion in Information Retreival: Rank vs. Score Combination. 2002, DIMACS TR 2002-58.
13. Heydermann, M.C., Cayley graphs and interconnection networks, in Graph Symmetry, G. Hahn, Sabiclussi, G., Editor. 1997, Kluwer Academic. p. 161-224.
14. Marden, J.I., Analysing and Modeling Rank Data. 1995: Chapman & Hall.
15. Parker, J.R., Multiple Sensors, Voting Methods and Target Value Analysis. 1998, Univ. of Calgary: Calgary Alberta CA.
16. Isard, M., Blake, A. Contour tracking by stochastic propagation of conditional density. in European Conf. on Computer Vision. 1996. Cambridge UK.
17. Collins, R.T., Lipton, A.J., Kanade, T. A System for Video Surveillance and Monitoring. in Proc. American Nuclear Society 8th Int. Topical Meeting on Robotics and Remote Systems. 1999.
18. Brodsky, T., Cohen, R., Cohen-Solal, E., Gutta, S., Lyons, D., Philomin, V., Trajkovic, M. Visual Surveillance in Retail Stores and in the Home. in Proc. European Workshop on Advanced Video Surveillance. 2001. Kingsten on Thames UK.
19. Elgammal, A., Harwood, D., Davis, L.S.,. Nonparametric Model for Background Subtraction. in Proc. 6th European Conference on Computer Vision. 2000.
20. Courtney, J.D., Automatic Video Indexing via Object Motion Analysis. Pattern Recognition, 1997. 30(4): p. 607-625.