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Multi-Targets Tracking Based On Bipartite Graph Matching Cover

Multi-Targets Tracking Based On Bipartite Graph Matching

Cybernetics and Information Technologies
Volume 14 (2014): Issue 5 (December 2014)
By: Jinqin Zhong,  Jieqing Tan,  Yingying Li,  Lichuan Gu and  Guolong Chen  
Open Access
|Dec 2014

References

  1. 1. Li, Zhang, Yuan Li, R. Nevatia. Global Data Association for Multi-Object Tracking Using Network Flows. - In: IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, 2008, 1-8.10.1109/CVPR.2008.4587584
    Search in Google Scholar
  2. 2. Bibby, C., I. Reid. Real-Time Tracking of Multiple Occluding Targets Using Level Sets. - In: IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010, 1307-1314.10.1109/CVPR.2010.5539818
    Search in Google Scholar
  3. 3. Huang, Chang, Yuan Li, R. Nevatia. Multiple Target Tracking by Learning-Based Hierarchical Association of Detection Responses. - IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, 2013, No 4, 898-910.10.1109/TPAMI.2012.15923428432
    Search in Google Scholar
  4. 4. Andriyenko, A., K. Schindler. Multi-Target Tracking by Continuous Energy Minimization. - In: IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, 2011, 1265-1272.10.1109/CVPR.2011.5995311
    Search in Google Scholar
  5. 5. Comaniciu, D., V. Ramesh, P. Meer. The Variable Bandwidth Mean Shift and Data- Driven Scale Selection. - In: IEEE International Conference on Computer Vision,Vancouver, BC, 2001, 438-445.
    Search in Google Scholar
  6. 6. Tomasi, C., T. Kanade. Detection and Tracking of Point Features. Technical Report CMUCS-91-132, Carnegie Mellon University, Pittsburgh, PA, 1991.
    Search in Google Scholar
  7. 7. Zhao, T., R. Nevatia. Tracking Multiple Humans in Complex Situation. - IEEE Transactions on Analysis and Machine Intelligence, Vol. 26, 2004, No 9, 1208-1221.10.1109/TPAMI.2004.7315742895
    Search in Google Scholar
  8. 8. Reid, D. An Algorithm for Tracking Multiple Targets. - IEEE Transactions on Automatic Control, Vol. 24, 1979, No 6, 8430-854.10.1109/TAC.1979.1102177
    Search in Google Scholar
  9. 9. Barshalom, Y., T. Fortmann. Tracking and Data Association. San Diego, Academic Press,1988.
    Search in Google Scholar
  10. 10. Goodman, I. R., R. Mahler, H. T. Nguyen. Mathematics of Data Fusion. Norwell, MA, Kluwer Academic Press, 1997.10.1007/978-94-015-8929-1
    Search in Google Scholar
  11. 11. Mahler, R. P. S., M. Lockheed. Multi Target Bayes Filter via First-Order Multi Target Moments. - IEEE Transactions on Aerospace and Electronic Systems, Vol. 39, 2003, No 4, 1152-1178.10.1109/TAES.2003.1261119
    Search in Google Scholar
  12. 12. Wu, Zheng, A. Thangali, S. Sclaroff, M. Betke. Coupling Detection and Data Association for Multiple Target Tracking. - In: IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, 2012, 1948-1955.10.1109/CVPR.2012.6247896
    Search in Google Scholar
  13. 13. Vo, Ba-Ngu, Wing-Kin Ma. The Gaussian Mixture Probability Hypothesis Density Filter. - IEEE Transaction on Signal Processing, Vol. 54, 2006, No 11, 4091-4104.10.1109/TSP.2006.881190
    Search in Google Scholar
  14. 14. Wang, Y. D., J. K. Wu, A. A. Kassim, W. M. Huang. Date-Driven Probability Hypothesis Density Filter for Visual Tracking. - IEEE Transaction on Circuits and Systems for Video Technology, Vol. 18, 2008, No 8, 1085-1095.10.1109/TCSVT.2008.927105
    Search in Google Scholar
  15. 15. Caetano, T. S., J. J. Mcauley, Li Cheng et al. Learning Graph Matching. - IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 31, 2009, No 6, 1048-1058.10.1109/TPAMI.2009.2819372609
    Search in Google Scholar
  16. 16. Duchenne, O., F. Bach, Kweon In-So, J. Ponce. A Tensor-Based Algorithm for High- Order Graph Matching. - IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 33, 2011, No 12, 2383-2395.10.1109/TPAMI.2011.11021646677
    Search in Google Scholar
  17. 17. Taeg, Sang Cho, S. Avidan, W. T. Freeman. A Probabilistic Image Jigsaw Puzzle Solver. - In: IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, 2011, 183-190.
    Search in Google Scholar
  18. 18. Yang, Xingwei, N. Adluru, L. J. Latechi. Particle Filter with State Permutations for Solving Image Jigsaw Puzzles. - In: IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, 2011, 2873-2880.10.1109/CVPR.2011.5995535508312327795660
    Search in Google Scholar
  19. 19. Grundmann, M., V. Dwatra, Han Mei, I. Essa. Efficient Hierarchical Graph-Based Video Segmentation. - In: IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010, 2141-2148.10.1109/CVPR.2010.5539893
    Search in Google Scholar
  20. 20. Hu, Nan, R. M. Rustamov, L. Guibas. Graph Matching with Anchor Nodes: A Learning Approach. - In: IEEE Conference on Computer Vision and Pattern Recognition, Portland, OR, 2013, 2096-2104.
    Search in Google Scholar
DOI: https://doi.org/10.2478/cait-2014-0045 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
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Language: English
Page range: 78 - 87
Published on: Dec 30, 2014
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Multi-target tracking,
bipartite graph optimal matching,
target interaction,
merging and splitting
Related subjects:
Computer sciences,
Information technology

© 2014 Jinqin Zhong, Jieqing Tan, Yingying Li, Lichuan Gu, Guolong Chen, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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