Predicting social interactions for visual tracking

BMVC 2011 - Proceedings of the British Machine Vision Conference 2011

Volumn , Issue , 2011, Pages

  Yan, Xu ^a   Kakadiaris, Ioannis A ^a   Shah, Shishir K ^a  

^a University of Houston   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; SECURITY SYSTEMS; SOCIAL SCIENCES;

AUTO REGRESSIVE MODELS; CONSTANT VELOCITIES; HUMAN INTERACTION MODEL; INTERACTIVE MARKOV CHAINS; OUTDOOR ENVIRONMENT; PEDESTRIAN TRACKING; SOCIAL INTERACTIONS; TRADITIONAL APPROACHES;

TRACKING (POSITION);

EID: 84898421786     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C25.102     Document Type: Conference Paper

References (16)

1. Behave interactions test case scenarios, October 2007. URL http://groups.inf.ed.ac.uk/vision/BEHAVEDATA/INTERACTIONS/.
2. M. Andriluka, S. Roth, and B. Schiele. People-tracking-by-detection and people-detection-by-tracking. In Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 1-8, Alaska, June 2008.
3. K. Bernardin and R. Stiefelhagen. Evaluating multiple object tracking performance: the CLEAR MOT metrics. Journal on Image and Video Processing, 2008:1-10, 2008.
4. C.W. Chen, R.C. Ugarte, C. Wu, and H. Aghajan. Discovering social interaction in real work environments. In Proc. International Workshop on Social Behavior Analysis, pages 1-6, Santa Barbara, March 2011.
5. W. Choi and S. Savarese. Multiple target tracking in world coordinate with single, minimally calibrated camera. In Proc. European Conference on Computer Vision, pages 553-567, Crete, Greece, September 2010.
6. J. Corander, M. Ekdahl, and T. Koski. Parallel interacting MCMC for learning of topologies of graphical models. Data Mining and Knowledge Discovery, 17(3):431-456, 2008.
7. F. Fleuret, J. Berclaz, R. Lengagne, and P. Fua. Multi-camera people tracking with a probabilistic occupancy map. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2):267-282, February 2008.
8. W.K. Hastings. Monte Carlo sampling method using Markov Chains and their applications. Biometrika, 57(1):97-109, 1970.
9. D. Helbing and P. Molnár. Social force model for pedestrian dynamics. Physical Review E, 51(5):4282-4286, 1995.
10. Z. Khan, T. Balch, and F. Dellaert. MCMC-based particle filtering for tracking a variable number of interacting targets. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(11):1805-1818, 2005.
11. J. Kwon and K.M. Lee. Visual tracking decomposition. In Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 1269-1272, San Francisco, June 2010.
12. M. Luber, J.A. Stork, G.D. Tipaldi, and K.O. Arras. People tracking with human motion prediction from social forces. In Proc. International Conference on Robotics and Automation, pages 464-469, Alaska, May 2010.
13. D. Mitzel, E. Horbert, A. Ess, and B. Leibe. Multi-person tracking with sparse detection and continuous segmentation. In Proc. European Conference on Computer Vision, pages 397-410, Crete, Greece, September 2010.
14. K. Okuma, A. Taleghani, and N.D. Freitas. A boosted particle filter: multitarget detection and tracking. In Proc. European Conference on Computer Vision, pages 28-39, Prague, Czech Republic, May 2004.
15. S. Pellegrini, A. Ess, K. Schindler, and L. van Gool. You'll never walk alone: modeling social behavior for multi-target tracking. In Proc. International Conference on Computer Vision, pages 261-268, Kyoto, Japan, 2009.
16. P. Perez, C. Hue, J. Vermaak, and M. Gangnet. Color-based probabilistic tracking. In Proc. European Conference on Computer Vision, pages 661-675, Copenhagen, Denmark, May 2002.