Abstract
We propose a combination of algorithms called the Kalman particle filter (KPF) that overcomes the object tracking occlusion problem in image processing while also achieving a reasonable computation time. When object occlusion occurs while using a Kalman filter (KF), we switch to the particle filter (PF) to track the object until the system is stable, and then switch back to the KF. We compared the results of running each algorithm (KF, PF, and KPF), independently, executed 30 times; the tracking performance was evaluated using six different methods. We found that KPF successfully addressed the occlusion problem, providing accurate estimates using highly efficient operations.
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References
Y.-L. Tian, M. Lu, A. Hampapur., in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05) (2005)
J. Zhu, Y. Lao, Y.F. Zheng, IEEE Trans. Circuits Syst. Video Technol. 20(2), 223–235 (2009)
R. Vullings, B. De Vries, J.W. Bergmans, IEEE Trans. Biomed. Eng. 58(4), 1094–1103 (2010)
E. Maggio, F. Smerladi, A. Cavallaro, IEEE Trans. Circuits Syst. Video Technol. 17(10), 1348–1359 (2007)
A. Jazayeri et al., IEEE Trans. Intell. Transp. Syst. 12(2), 583–595 (2011)
T. Xiong, C. Debrunner, IEEE Trans. Intell. Transp. Syst. 5(4), 324–328 (2004)
D. Comaniciu, V. Ramesh, P. Meer., in Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No. PR00662) (2000)
J.L. Barron, D.J. Fleet, S.S. Beauchemin, Int. J. Comput. Vision 12(1), 43–77 (1994)
A. Czyzewski, P. Dalka., in 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)
M.Z. Islam, C.-M. Oh, C.-W. Lee, Int. J. Signal Process., Image Process. Pattern, 2(1) (2009)
T. Zhang, et al., in 2008 International Conference on Intelligent Computation Technology and Automation (ICICTA) (2008)
J. Wang, et al., in 2010 2nd International Conference on Advanced Computer Control (2010)
X. Li, et al., in The 2010 IEEE International Conference on Information and Automation (2010)
N. Peterfreund, IEEE Trans. Pattern Anal. Mach. Intell. 21(6), 564–569 (1999)
Y. Wu, T.S. Huang, Int. J. Comput. Vision 58(1), 55–71 (2004)
M. Isard, A. Blake, Int. J. Comput. Vision 29(1), 5–28 (1998)
C. Yang, R. Duraiswami, L. Davis, in Tenth IEEE International Conference on Computer Vision (ICCV’05), 1 (2005)
J.S. Liu, R. Chen, J. Am. Stat. Assoc. 93(443), 1032–1044 (1998)
S. Maskell, N. Gordon, Target Tracking: Algorithms and Applications (Ref. No. 2001/174), IEE, 2, 21–215 (2001)
X. Fu, Y. Jia, IEEE Trans. Signal Process. 58(10), 5414–5420 (2010)
X. Fu, et al., in Proceedings of the 2010 American Control Conference (2010)
N. Bouaynaya, D. Schonfeld, IEEE Trans. Circuits Syst. Video Technol. 19(7), 1068 (2009)
A. Abdel-Hadi, in The 2010 International Conference on Computer Engineering and Systems (2010)
P. Chen et al., IET Image Proc. 5(5), 440–447 (2011)
T. Xiong, C. Debrunner., in International Conference on Computer Analysis of Images and Patterns (2003)
S. Nigam, A. Khare, IET Comput. Vision 6(3), 231–251 (2012)
A. Ichigaya et al., IEEE Trans. Circuits Syst. Video Technol. 16(2), 251–259 (2006)
Acknowledgements
We thank Jia-Yu Chen and Jung-Ting Hsieh for editing technical supports. This study was supported financially, in part, by grant from MOST-107-2221-E-992-014-MY2.
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Lan, JH. et al. (2020). Combining the Kalman Filter and Particle Filter in Object Tracking to Avoid Occlusion Problems. In: Parinov, I., Chang, SH., Long, B. (eds) Advanced Materials. Springer Proceedings in Materials, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-030-45120-2_47
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DOI: https://doi.org/10.1007/978-3-030-45120-2_47
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