
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Alessio Dore, Carlo Regazzoni, "Interaction Analysis with a Bayesian Trajectory Model," IEEE Intelligent Systems, vol. 25, no. 3, pp. 3240, May/June, 2010.  
BibTex  x  
@article{ 10.1109/MIS.2010.37, author = {Alessio Dore and Carlo Regazzoni}, title = {Interaction Analysis with a Bayesian Trajectory Model}, journal ={IEEE Intelligent Systems}, volume = {25}, number = {3}, issn = {15411672}, year = {2010}, pages = {3240}, doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2010.37}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  MGZN JO  IEEE Intelligent Systems TI  Interaction Analysis with a Bayesian Trajectory Model IS  3 SN  15411672 SP32 EP40 EPD  3240 A1  Alessio Dore, A1  Carlo Regazzoni, PY  2010 KW  Interaction analysis KW  Dynamic Bayesian Networks KW  trajectory analysis KW  activity recognition KW  intelligent systems VL  25 JA  IEEE Intelligent Systems ER   
A Dynamic Bayesian Network model uses the Instantaneous Topological Map algorithm to process couples of observed interacting trajectories. It recognizes human interactions through the analysis of their patterns of movement.
1. K.P. Murphy, "Dynamic Bayesian Networks: Representation, Inference and Learning," doctoral dissertation, Univ. of Calif, Berkeley, 2002.
2. J. Jockusch and H. Ritter, "An Instantaneous Topological Map for Correlated Stimuli," Proc. Int'l Joint Conf. Neural Networks, IEEE Press, vol. 1, 1999, pp. 529–534.
3. A. Dore, A.F. Cattoni, and C.S. Regazzoni, "Interaction Modeling and Prediction in Smart Spaces: A Bioinspired Approach Based on Autobiographical Memory," to be published in IEEE Trans. Systems, Man, and Cybernetics, Part A, 2010.
4. A.R. Damasio, The Feeling of What Happens: Body, Emotion and the Making of Consciousness, Harvest Books, 2000.
5. S. Scheding, R. Grover, and H. DurrantWhyte, "Machine Perception in Unstructured and Unknown Environments," Robotics and Cognitive Approaches to Spatial Mapping, Springer, 2008, pp. 65–81.
6. T.M. Martinetz, "Competitive Hebbian Learning Rule Forms Perfectly Topology Preserving Maps," Proc. Int'l Conf. Artificial Neural Networks (ICANN 93), IEEE Press, 1993, pp. 427–434.
7. T. Martinetz and K. Schulten, "A 'NeuralGas' Network Learns Topologies," Artificial Neural Networks, vol. I, 1991, pp. 397–402.
8. M.A.T. Figueiredo and A.K. Jain, "Unsupervised Learning of Finite Mixture Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 3, 2002, pp. 381–396.
9. A. Dore and C.S. Regazzoni, "Bayesian Bioinspired Model for Learning Interactive Trajectories," Proc. Int'l Conf. Advanced Video and Signal Based Surveillance (AVSS 09), IEEE CS Press, 2009, pp. 207–212.
10. N. Oliver, B. Rosario, and A. Pentland, "A Bayesian Computer Vision System for Modeling Human Interactions," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, 2000, pp. 831–843.
11. Y. Du, F. Chen, and W. Xu, "Human Interaction Representation and Recognition through Motion Decomposition," IEEE Signal Processing Letters, vol. 14, no. 12, 2007, pp. 952–955.
12. X. Ma et al., "Event Analysis Based on Multiple Interactive Motion Trajectories," IEEE Trans. Circuits and Systems for Video Technology, vol. 19, no. 3, 2009, pp. 397–406.
1. T. Xiang and S. Gong, "Video Behavior Profiling for Anomaly Detection," IEEE Trans. Pattern Analysis Machine Intelligence, vol. 30, no. 5, 2008, pp. 893–908.
2. A. Prati, S. Calderara, and R. Cucchiara, "Using Circular Statistics for Trajectory Shape Analysis," Proc. Int'l Conf. Computer Vision and Pattern Recognition (CVPR 08), IEEE CS Press, 2008, pp. 1–8.
3. C. Laugier et al., "Geometric and Bayesian Models for Safe Navigation in Dynamic Environments," J. Intelligent Service Robotics, vol. 1, no. 1, 2008, pp. 51–72.
4. F. Porikli and T. Haga, "Event Detection by Eigenvector Decomposition Using Object and Frame Features," Proc. 2004 Conf. Computer Vision and Pattern Recognition Workshop (CVPRW 04), IEEE CS Press, 2004, p. 114.
5. C. Piciarelli, C. Micheloni, and G.L. Foresti, "TrajectoryBased Anomalous Event Detection," IEEE Trans. Circuits and Systems for Video Technology, vol. 18, no. 11, 2008, pp. 1544–1554.
6. J. Kruskal and M. Liberman, The Symmetric TimeWarping Problem: From Continuous to Discrete, AddisonWesley, 1983.
7. R.J. Morris and D.C. Hogg, "Statistical Models of Object Interaction," Int'l J. Computer Vision, vol. 37, no. 2, 2000, pp. 209–215.
8. N. Oliver, B. Rosario, and A. Pentland, "A Bayesian Computer Vision System for Modeling Human Interactions," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, 2000, pp. 831–843.
9. Y. Du, F. Chen, and W. Xu, "Human Interaction Representation and Recognition through Motion Decomposition," IEEE Signal Processing Letters, vol. 14, no. 12, 2007, pp. 952–955.
10. X. Ma, F. Bashir, A. Khokhar, and D. Schonfeld, "Event Analysis Based on Multiple Interactive Motion Trajectories," IEEE Trans. Circuits and Systems for Video Technology, vol. 19, no. 3, 2009, pp. 397–406.
11. A. Dore and C.S. Regazzoni, "Bayesian Bioinspired Model for Learning Interactive Trajectories," Proc. Int'l Conf. Advanced Video and Signal Based Surveillance (AVSS 09), IEEE CS Press, 2009, pp. 207–212.