Applying particle filter technology to object tracking

Tun Chang Lu, Shun Peng Hsu, Yu Xian Huang, Yi-Nung Chung, Shi Ming Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study proposes an approach to track moving objects and to predict the observed targets based on the particle filter. This system includes three parts which are the foreground segmentation, the partial filtering, and the particle filter for tracking objects. In order to estimate the location of next state and track the moving objects, it applies the prior and current state based on the particle filter technology. Experimental result shows that this method can track objects accurately.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014
EditorsJengnan Juang
PublisherSpringer Verlag
Pages105-111
Number of pages7
ISBN (Print)9783319173139
DOIs
Publication statusPublished - 2016 Jan 1
Event3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014 - Kaohsiung, Taiwan
Duration: 2014 Dec 192014 Dec 21

Publication series

NameLecture Notes in Electrical Engineering
Volume345
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

Other3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014
CountryTaiwan
CityKaohsiung
Period14-12-1914-12-21

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

Cite this

Lu, T. C., Hsu, S. P., Huang, Y. X., Chung, Y-N., & Chen, S. M. (2016). Applying particle filter technology to object tracking. In J. Juang (Ed.), Proceedings of the 3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014 (pp. 105-111). (Lecture Notes in Electrical Engineering; Vol. 345). Springer Verlag. https://doi.org/10.1007/978-3-319-17314-6_14
Lu, Tun Chang ; Hsu, Shun Peng ; Huang, Yu Xian ; Chung, Yi-Nung ; Chen, Shi Ming. / Applying particle filter technology to object tracking. Proceedings of the 3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014. editor / Jengnan Juang. Springer Verlag, 2016. pp. 105-111 (Lecture Notes in Electrical Engineering).
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Lu, TC, Hsu, SP, Huang, YX, Chung, Y-N & Chen, SM 2016, Applying particle filter technology to object tracking. in J Juang (ed.), Proceedings of the 3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014. Lecture Notes in Electrical Engineering, vol. 345, Springer Verlag, pp. 105-111, 3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014, Kaohsiung, Taiwan, 14-12-19. https://doi.org/10.1007/978-3-319-17314-6_14

Applying particle filter technology to object tracking. / Lu, Tun Chang; Hsu, Shun Peng; Huang, Yu Xian; Chung, Yi-Nung; Chen, Shi Ming.

Proceedings of the 3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014. ed. / Jengnan Juang. Springer Verlag, 2016. p. 105-111 (Lecture Notes in Electrical Engineering; Vol. 345).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - This study proposes an approach to track moving objects and to predict the observed targets based on the particle filter. This system includes three parts which are the foreground segmentation, the partial filtering, and the particle filter for tracking objects. In order to estimate the location of next state and track the moving objects, it applies the prior and current state based on the particle filter technology. Experimental result shows that this method can track objects accurately.

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Lu TC, Hsu SP, Huang YX, Chung Y-N, Chen SM. Applying particle filter technology to object tracking. In Juang J, editor, Proceedings of the 3rd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2014. Springer Verlag. 2016. p. 105-111. (Lecture Notes in Electrical Engineering). https://doi.org/10.1007/978-3-319-17314-6_14