Multi-commodity network flow for tracking multiple people

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 36, Issue 8, 2014, Pages 1614-1627

  Shitrit, Horesh Ben ^a   Berclaz, Jerome ^b   Fleuret, Francois ^a,c   Fua, Pascal ^a  

^a EPFL   (Switzerland)

^b MICROSOFT   (United States)

^c IDIAP RESEARCH INSTITUTE   (Switzerland)

Author keywords

Linear Programming; MCNF; Multi Commodity Network Flow; Multi object tracking; Tracklet association

Indexed keywords

IMAGE MATCHING; LINEAR PROGRAMMING; REAL TIME CONTROL;

COMPLEX SEQUENCES; IMAGE APPEARANCE; MCNF; MULTI-COMMODITY NETWORK FLOWS; MULTI-OBJECT TRACKING; REAL-TIME IMPLEMENTATIONS; TRACKING ALGORITHM; TRACKLET ASSOCIATIONS;

SPORTS;

EID: 84891805704     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.210     Document Type: Article

References (58)

1. M. Breitenstein, F. Reichlin, B. Leibe, E. Koller-Meier, and L. Van Gool, "Online multi-person tracking-by-detection from a single uncalibrated camera," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 9, pp. 1820-1833, Sept. 2010.
2. J. Wolf, A. Viterbi, and G. Dixon, "Finding the best set of K paths through a trellis with application to multitarget tracking," IEEE Trans. Aerosp. Electron. Syst., vol. 25, no. 2, pp. 287-296, Mar. 1989.
3. F. Fleuret, J. Berclaz, R. Lengagne, and P. Fua, "Multi-camera people tracking with a probabilistic occupancy map," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 2, pp. 267-282, Feb. 2008.
4. P. Storms and F. Spieksma, "An LP-based algorithm for the data association problem in multitarget tracking," Comput. Operat. Res., vol. 30, no. 7, pp. 1067-1085, June 2003. (Pubitemid 36270656)
5. H. Jiang, S. Fels, and J. Little, "A linear programming approach for multiple object tracking," in Proc. CVPR, Minneapolis, MN, USA, 2007.
6. A. Perera, C. Srinivas, A. Hoogs, G. Brooksby, and H. Wensheng, "Multi-object tracking through simultaneous long occlusions and split-merge conditions," in Proc. CVPR, Washington, DC, USA, 2006.
7. L. Zhang, Y. Li, and R. Nevatia, "Global data association for multiobject tracking using network flows," in Proc. CVPR, Anchorage, AK, USA, 2008.
8. H. Pirsiavash, D. Ramanan, and C. Fowlkes, "Globally-optimal greedy algorithms for tracking a variable number of objects," in Proc. CVPR, Colorado Springs, CO, USA, 2011 [Online]. Available: http://www.ics.uci.edu/ %7edramanan/
9. J. Berclaz, F. Fleuret, E. Türetken, and P. Fua, "Multiple object tracking using K-shortest paths optimization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 9, pp. 1806-1819, Sept. 2011.
10. J. W. Suurballe, "Disjoint paths in a network," Networks, vol. 4, no. 2, pp. 125-145, 1974.
11. T. Misu, A. Matsui, S. Clippingdale, M. Fujii, and N. Yagi, "Probabilistic integration of tracking and recognition of soccer players," in Advances in Multimedia Modeling, Berlin, Germany: Springer, 2009.
12. H. BenShitrit, J. Berclaz, F. Fleuret, and P. Fua, "Tracking multiple people under global appearance constraints," in Proc. IEEE ICCV, Barcelona, Spain, 2011.
13. M. Andriluka, S. Roth, and B. Schiele, "People-tracking-bydetection and people-detection-by-tracking," in Proc. CVPR, Anchorage, AK, USA, 2008.
14. A. Andriyenko and K. Schindler, "Globally optimal multi-target tracking on a hexagonal lattice," in Proc. ECCV, Berlin, Germany, 2010.
15. S. Blackman, Multiple-Target Tracking with Radar Applications. Dedham, MA, USA: Artech House, 1986.
16. J. Black, T. Ellis, and P. Rosin, "Multi-view image surveillance and tracking," in Proc. IEEE Workshop Motion Video Computing, Washington, DC, USA, 2002.
17. A. Mittal and L. Davis, "M2Tracker: A multi-view approach to segmenting and tracking people in a cluttered scene," Int. J. Comput. Vision, vol. 51, no. 3, pp. 189-203, 2003.
18. S. Iwase and H. Saito, "Parallel tracking of all soccer players by integrating detected positions in multiple view images," in Proc. ICPR, Washington, DC, USA, 2004.
19. M. Xu, J. Orwell, and G. Jones, "Tracking football players with multiple cameras," in Proc. ICIP, 2004.
20. D. R. Magee, "Tracking multiple vehicles using foreground, background and motion models," Image Vision Comput., vol. 22, no. 2, pp. 143-155, Feb. 2004.
21. J. Giebel, D. Gavrila, and C. Schnorr, "A Bayesian framework for multi-cue 3D object tracking," in Proc. ECCV, Prague, Czech Republic, 2004.
22. K. Smith, D. Gatica-Perez, and J.-M. Odobez, "Using particles to track varying numbers of interacting people," in Proc. CVPR, 2005.
23. K. Okuma, A. Taleghani, N. de Freitas, J. Little, and D. Lowe, "A boosted particle filter: Multitarget detection and tracking," in Proc. ECCV, Prague, Czech Republic, May 2004.
24. Z. Khan, T. Balch, and F. Dellaert, "MCMC-based particle filtering for tracking a variable number of interacting targets," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 11, pp. 1805-1819, Nov. 2005. (Pubitemid 41685115)
25. C. Yang, R. Duraiswami, and L. Davis, "Fast multiple object tracking via a hierarchical particle filter," in Proc. ICCV, Washington, DC, USA, 2005.
26. T. Mauthner, M. Donoser, and H. Bischof, "Robust tracking of spatial related components," in Proc. ICPR, Tampa, FL, USA, 2008.
27. D. B. Reid, "An algorithm for tracking multiple targets," IEEE Trans. Autom. Control, vol. 24, no. 6, pp. 843-854, Dec. 1979.
28. S. Oh, S. Russell, and S. Sastry, "Markov chain Monte Carlo data association for general multiple-target tracking problems," in Proc. 43rd IEEE CDC, Nassau, Bahamas, 2004.
29. W. Ge and R. T. Collins, "Multi-target data association by tracklets with unsupervised parameter estimation," in Proc. BMVC, 2008.
30. C. Wojek, S. Walk, S. Roth, and B. Schiele, "Monocular 3D scene understanding with explicit occlusion reasoning," in Proc. CVPR, Providence, RI, USA, 2011.
31. C. Wojek, S. Walk, S. Roth, K. Schindler, and B. Schiele, "Monocular visual scene understanding: Understanding multiobject traffic scenes," IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 4, pp. 882-897, Apr. 2013.
32. A. Andriyenko, K. Schindler, and S. Roth, "Discrete-continuous optimization for multi-target tracking," in Proc. CVPR, Providence, RI, USA, 2012.
33. S. W. Joo and R. Chellappa, "A multiple-hypothesis approach for multiobject visual tracking," IEEE Trans. Image Process., vol. 16, no. 11, pp. 2849-2854, Nov. 2007. (Pubitemid 350141857)
34. V. K. Singh, B. Wu, and R. Nevatia, " Pedestrian tracking by associating tracklets using detection residuals," in Proc. IEEE Workshop Motion Video Computing, Copper Mountain, CO, USA, 2008.
35. Y. Li, C. Huang, and R. Nevatia, "Learning to associate: Hybridboosted multi-target tracker for crowded scene," in Proc. CVPR, Miami, FL, USA, 2009.
36. C.-H. Kuo, C. Huang, and R. Nevatia, "Multi-target tracking by on-line learned discriminative appearance models," in Proc. CVPR, San Francisco, CA, USA, 2010.
37. C.-H. Kuo and R. Nevatia, "How does person identity recognition help multi-person tracking?" in Proc. CVPR, Providence, RI, USA, 2011.
38. J. Shin, L. J. Guibas, and F. Zhao, "A distributed algorithm for managing multi-target identities in wireless ad-hoc sensor networks information processing in sensor networks," in Proc. IPSN, Palo Alto, CA, USA, 2003.
39. R. Kondor, A. Howard, and T. Jebara, "Multi-object tracking with representations of the symmetric group," in Proc. AISTATS, 2007.
40. J. Huang, C. Guestrin, and L. Guibas, "Fourier theoretic probabilistic inference over permutations," J. Mach. Learn. Res., vol. 10, pp. 997-1070, May 2009.
41. J. F. Henriques, R. Caseiro, and J. Batista, "Globally optimal solution to multi-object tracking with merged measurements," in Proc. ICCV, 2011.
42. B. Yang, C. Huang, and R. Nevatia, "Learning affinities and dependencies for multi-target tracking using a CRF model," in Proc. CVPR, Providence, RI, USA, 2011.
43. B. Yang and R. Nevatia, "An online learned CRF model for multitarget tracking," in Proc. CVPR, Providence, RI, USA, 2012.
44. W. Choi and S. Savarese, "A unified framework for multitarget tracking and collective activity recognition," in Proc. ECCV, Florence, Italy, 2012.
45. A. Ellis, A. Shahrokni, and J. Ferryman, "Pets 2009 and winter Pets 2009 results, a combined evaluation," in Proc. PETS, Snowbird, UT, USA, Dec. 2009.
46. Z. Wu, A. Thangali, S. Sclaroff, and M. Betke, "Coupling detection and data association for multiple object tracking," in Proc. CVPR, Providence, RI, USA, 2012.
47. L. Leal-Taixe, G. Pons-Moll, and B. Rosenhahn, "Branch-and-price global optimization for multi-view multi-target tracking," in Proc. CVPR, Providence, RI, USA, 2012.
48. D. Delannay, N. Danhier, and C. Vleeschouwer, "Detection and recognition of sports(wo)men from multiple views," in Proc. ICDSC, Como, Italy, 2009.
49. W.-L. Lu, J.-A. Ting, K. P. Murphy, and J. J. Little, "Identifying players in broadcast sports videos using conditional random fields," in Proc. CVPR, Providence, RI, USA, 2011.
50. C. Li, S. T. McCormick, and D. Simchi-Levi, "Finding disjoint paths with different path-costs: Complexity and algorithms," Networks, vol. 22, no. 7, pp. 653-667, 1992.
51. M. S. Bazaraa, J. J. Jarvis, and H. D. Sherali, Linear Programming and Network Flows. Hoboken, NJ, USA: Wiley, 2010.
52. D. Choi and I. Choi, "On the effectiveness of the linear programming relaxation of the 0-1 multi-commodity minimum cost network flow problem," in Proc. COCOON, Taipei, Taiwan, 2006.
53. T. D'Orazio, M. Leo, N. Mosca, P. Spagnolo, and P. L. Mazzeo, "A semi-automatic system for ground truth generation of soccer video sequences," in Proc. Int. Conf. Advanced Video Signal Based Surveillance, Genova, Italy, 2009.
54. C. Poppe, S. D. Bruyne, S. Verstockt, and R. V. de Walle, "Multicamera analysis of soccer sequences," in Proc. Int. Conf. Advanced Video Signal Based Surveillance, Boston, MA, USA, 2010.
55. The Mosek Optimization Tools. (2010) [Online]. Available: http://www.mosek.com/
56. K. Bernardin and R. Stiefelhagen, "Evaluating multiple object tracking performance: The CLEAR MOT metrics," EURASIP J. Image Video Process., vol. 2008, Article 246309, May 2008.
57. R. Kasturi et al., "Framework for performance evaluation of face, text, and vehicle detection and tracking in video: Data, metrics, and protocol," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 2, pp. 319-336, Feb. 2009.
58. H. Kuhn, "The Hungarian method for the assignment problem," Nav. Res. Logist. Quart., vol. 2, no. 1-2, pp. 83-97, Mar. 1955.