Crowd behavior analysis under cameras network fusion using probabilistic methods

13th Conference on Information Fusion, Fusion 2010

Volumn , Issue , 2010, Pages

  Drews Jr , P ^a   Quintas, J ^a   Dias, J ^a   Andersson, M ^b   Nygards J ^b   Rydell, J ^b  

^a UNIVERSITY OF COIMBRA   (Portugal)

^b SWEDISH DEFENCE RESEARCH AGENCY   (Sweden)

Author keywords

Bayesian networks; Behavior analysis; Hidden Markov models; Sensor fusion

Indexed keywords

AUTOMATIC SYSTEMS; BEHAVIOR ANALYSIS; CAMERA NETWORK; CROWD ANALYSIS; CROWD BEHAVIOR; LOW COSTS; MANUAL ANALYSIS; NETWORK FUSION; PROBABILISTIC METHODS; PUBLIC PLACES; ROBUST METHODS; SENSOR FUSION;

BEHAVIORAL RESEARCH; CAMERAS; DISTRIBUTED PARAMETER NETWORKS; HIDDEN MARKOV MODELS; INFERENCE ENGINES; INFORMATION FUSION; INTELLIGENT NETWORKS; OPTICAL FLOWS; SECURITY SYSTEMS; SENSORS; SPEECH RECOGNITION;

BAYESIAN NETWORKS;

EID: 79952374358     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. J. Ahlberg, D. Arsic, T. Ganchev, A. Linderhed, P. Menezes, S. Ntalampiras, T. Olma, I. Potamitis, and J. Ros. Prometheus: Prediction and interpretation of human behavior based on probabilistic structures and heterogeneous sensors. In European Conference on Artificial Intelligence (ECAI), Patras, Greece, 2008.
2. S. Ali and M. Shah. A lagrangian particle dynamics approach for crowd flow segmentation and stability analysis. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1-6, 2007.
3. S. Ali and M. Shah. Floor fields for tracking in high density crowd scenes. In European Conference on Computer Vision (ECCV), pages 1-14, 2008.
4. M. Andersson, J. Rydell, and J. Ahlberg. Estimation of crowd behavior using sensor networks and sensor fusion. In International Conference on Information Fusion (FUSION '09), pages 396-403, 2009.
5. E. Andrade, S. Blunsden, and R. Fisher. Modelling crowd scenes for event detection. In International Conference on Pattern Recognition (ICPR), pages 175-178, Washington, DC, USA, 2006. IEEE Computer Society. (Pubitemid 46531871)
6. H. Ardö. Multi-target tracking using on-line Viterbi optimisation and stochastic Modelling. PhD thesis, Mathematical Sciences - Lund, 2009.
7. D. Arsic, J. Schenk, B. Schuller, F. Wallhoff, and G. Rigoll. Submotions for hidden markov model based dynamic facial action recognition. In IEEE International Conference on Image Processing, pages 673-676, 2006.
8. G. Brostow and R. Cipolla. Unsupervised Bayesian detection of independent motion in crowds. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 594-601, 2006. (Pubitemid 44931380)
9. F. Cupillard, F. Bremond, and M. Thonnat. Behaviour recognition for individuals, groups of people and crowd. In IEEE Symposium on Intelligence Distributed Surveillance Systems, pages 7/1 - 7/5, 2003.
10. D. Helbing and P. Molnar. Social force model for pedestrian dynamics. Physical Review E, 51:4282, 1995.
11. D. Knill and A. Pouget. The bayesian brain: the role of uncertainty in neural coding and computation. Trends in Neurosciences, 27(12):712-719, 2004. (Pubitemid 39488074)
12. N. MacFarlane and C. Schofield. Segmentation and tracking of piglets in images. Machine Vision and Applications, 8(3):187-193, 1995.
13. J. Marques, P. Jorge, A. Abrantes, and J. Lemos. Tracking groups of pedestrians in video sequences. In Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), volume 9, pages 101-108, 2003.
14. R. Mehran, A. Oyama, and M. Shah. Abnormal crowd behavior detection using social force model. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pages 935-942, Los Alamitos, CA, USA, 2009. IEEE Computer Society.
15. N. Pelechano and N. Allbeck, J.and Badler. Controlling individual agents in high-density crowd simulation. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA 07), pages 99-108, Aire-la-Ville, Switzerland, Switzerland, 2007. Eurographics Association.
16. L. Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Readings in speech recognition, pages 267-296, 1990.
17. P. Reisman, O. Mano, S. Avidan, and A. Shashua. Crowd detection in video sequences. In IEEE Intelligent Vehicles Symposium (IV2004), pages 66-71, 2004.
18. J. Rett, J. Dias, and J. Ahuactzin. Bayesian reasoning for laban movement analysis used in human machine interaction. Int. J. Reasoning based System, 1:64-74, 2008.
19. B. Zhan, D. Monekosso, P. Remagnino, S. Velastin, and L. Xu. Crowd analysis: a survey. Machine Vision Application, 19(5-6):345-357, 2008.
20. T. Zhao and R. Nevatia. Tracking multiple humans in complex situations. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 26(9):1208-1221, 2004.