Multiple hypothesis tracking of clusters of people

IEEE International Conference on Intelligent Robots and Systems

Volumn , Issue , 2006, Pages 692-697

  Mucientes, Manuel ^a   Burgard, Wolfram ^b  

^a UNIVERSITY OF SANTIAGO DE COMPOSTELA   (Spain)

^b UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; PROBLEM SOLVING; ROBUSTNESS (CONTROL SYSTEMS); TRACKING (POSITION);

MULTIPLE HYPOTHESIS TRACKING (MHT);

MOBILE ROBOTS;

EID: 34250682596     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2006.282614     Document Type: Conference Paper

References (12)

1. L. Taycher, J. Fisher, and T. Darrell, "Combining object and feature dynamics in probabilistic tracking," in Proc. Int. Conf. on Computer Vision and Pattern Recognition, 2005, pp. 106-113.
2. M. Rosencrantz, G. Gordon, and S. Thrun, "Locating moving entities in indoor environments with teams of mobile robots," in Proc. 2nd Int. Conf. on Autonom. Agents and Multiagent Syst., 2003, pp. 233-240.
3. D. Reid, "An algorithm for tracking multiple targets," IEEE Transactions on Automatic Control, vol. AC-24, no. 6, pp. 843-854, 1979.
4. I. Cox and S. Hingorani, "An efficient implementation of reid's multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking," IEEE T. Patt. Anal. Mach. Intell., vol. 18, pp. 138-150, 1996.
5. T. Schmitt, M. Beetz, R. Hanek, and S. Buck, "Watch their moves: Applying probabilistic multiple object tracking to autonomous robot soccer," in Proc. 18th Nat. Conf. on Artif. Intell., 2002, pp. 599-604.
6. H. Tao, H. Sawhney, and R. Kumar, "A sampling algorithm for tracking multiple objects," in Workshop on Vision Algorithms, 1999, pp. 53-68.
7. M. Isard and J. MacCormick, "Bramble: A bayesian multiple-blob tracker," in Proc. Int. Conf. Computer Vision, 2001, pp. 34-41.
8. G. Taylor and L. Kleeman, "A multiple hypothesis walking person tracker with switched dynamic model," in Proc. Australasian Conf. on Robotics and Automation, Canberra (Australia), 2004.
9. D. Schulz, W. Burgard, D. Fox, and A. Cremers, "People tracking with mobile robots using sample-based joint probabilistic data association filters." Int. J. of Robotics Research, vol. 22, no. 2, pp. 99-116, 2003.
10. K. Murty, "An algorithm for ranking all the assignments in order of increasing cost," Operations Research, vol. 16, pp. 682-687, 1968.
11. I. Cox and M. Miller, "On finding ranked assignments with application to multitarget tracking and motion correspondence," IEEE Tmnsactions on Aerospace and Electronic Systems, vol. 31, pp. 486-489, 1995.
12. T. Kurien, Multitarget-Multisensor Tracking: Advanced Applications. Norwood, MA (USA): Artech House, 1990, ch. Issues in the design of practical multitarget tracking algorithms, pp. 43-83.