An Anti-occlusion Video Target Tracking Method Based on Kalman Filter

Dang Kexin; Zhang Xiongfei; Chen Zhihong; Yang Ziwen; Li Chen

doi:doi:10.11648/j.jeee.20190702.17

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An Anti-occlusion Video Target Tracking Method Based on Kalman Filter

Dang Kexin, Zhang Xiongfei, Chen Zhihong, Yang Ziwen, Li Chen

Published in Journal of Electrical and Electronic Engineering (Volume 7, Issue 2)

Received: 14 April 2019 Published: 15 June 2019

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Abstract

The human visual system is the main component of the brain-based information processing system. It is the main way for humans to obtain external information. Therefore, the emerging science represented by computer vision came into being. Video-specific target tracking is a core issue in the field of computer vision research. It has been widely studied and concerned, and it has been widely used in many fields, such as video surveillance, intelligent navigation, medical diagnosis, augmented reality and virtual reality, etc. The specific moving target tracking algorithm and improved algorithm in the video are studied to some extent. Combining the meanshift algorithm with Kalman filtering can solve the occlusion problem of moving targets in complex scenes. This project intends to use Kalman filter and meanshift algorithm to detect and track the specified target in the video image sequence, and obtain the position, angle, scale, velocity, acceleration and dynamic trajectory of the target. Experiments show that this method has a good tracking effect on the target tracking in the video which is partially occluded during the motion.

Published in	Journal of Electrical and Electronic Engineering (Volume 7, Issue 2)
DOI	10.11648/j.jeee.20190702.17
Page(s)	69-74
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Computer Vision, Video Target Tracking, Kalman Filter, Signal Processing, Pattern Recognition

References

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APA Style

Dang Kexin, Zhang Xiongfei, Chen Zhihong, Yang Ziwen, Li Chen. (2019). An Anti-occlusion Video Target Tracking Method Based on Kalman Filter. Journal of Electrical and Electronic Engineering, 7(2), 69-74. https://doi.org/10.11648/j.jeee.20190702.17

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ACS Style

Dang Kexin; Zhang Xiongfei; Chen Zhihong; Yang Ziwen; Li Chen. An Anti-occlusion Video Target Tracking Method Based on Kalman Filter. J. Electr. Electron. Eng. 2019, 7(2), 69-74. doi: 10.11648/j.jeee.20190702.17

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AMA Style

Dang Kexin, Zhang Xiongfei, Chen Zhihong, Yang Ziwen, Li Chen. An Anti-occlusion Video Target Tracking Method Based on Kalman Filter. J Electr Electron Eng. 2019;7(2):69-74. doi: 10.11648/j.jeee.20190702.17

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@article{10.11648/j.jeee.20190702.17,
  author = {Dang Kexin and Zhang Xiongfei and Chen Zhihong and Yang Ziwen and Li Chen},
  title = {An Anti-occlusion Video Target Tracking Method Based on Kalman Filter},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {7},
  number = {2},
  pages = {69-74},
  doi = {10.11648/j.jeee.20190702.17},
  url = {https://doi.org/10.11648/j.jeee.20190702.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20190702.17},
  abstract = {The human visual system is the main component of the brain-based information processing system. It is the main way for humans to obtain external information. Therefore, the emerging science represented by computer vision came into being. Video-specific target tracking is a core issue in the field of computer vision research. It has been widely studied and concerned, and it has been widely used in many fields, such as video surveillance, intelligent navigation, medical diagnosis, augmented reality and virtual reality, etc. The specific moving target tracking algorithm and improved algorithm in the video are studied to some extent. Combining the meanshift algorithm with Kalman filtering can solve the occlusion problem of moving targets in complex scenes. This project intends to use Kalman filter and meanshift algorithm to detect and track the specified target in the video image sequence, and obtain the position, angle, scale, velocity, acceleration and dynamic trajectory of the target. Experiments show that this method has a good tracking effect on the target tracking in the video which is partially occluded during the motion.},
 year = {2019}
}

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TY - JOUR
T1 - An Anti-occlusion Video Target Tracking Method Based on Kalman Filter
AU - Dang Kexin
AU - Zhang Xiongfei
AU - Chen Zhihong
AU - Yang Ziwen
AU - Li Chen
Y1 - 2019/06/15
PY - 2019
N1 - https://doi.org/10.11648/j.jeee.20190702.17
DO - 10.11648/j.jeee.20190702.17
T2 - Journal of Electrical and Electronic Engineering
JF - Journal of Electrical and Electronic Engineering
JO - Journal of Electrical and Electronic Engineering
SP - 69
EP - 74
PB - Science Publishing Group
SN - 2329-1605
UR - https://doi.org/10.11648/j.jeee.20190702.17
AB - The human visual system is the main component of the brain-based information processing system. It is the main way for humans to obtain external information. Therefore, the emerging science represented by computer vision came into being. Video-specific target tracking is a core issue in the field of computer vision research. It has been widely studied and concerned, and it has been widely used in many fields, such as video surveillance, intelligent navigation, medical diagnosis, augmented reality and virtual reality, etc. The specific moving target tracking algorithm and improved algorithm in the video are studied to some extent. Combining the meanshift algorithm with Kalman filtering can solve the occlusion problem of moving targets in complex scenes. This project intends to use Kalman filter and meanshift algorithm to detect and track the specified target in the video image sequence, and obtain the position, angle, scale, velocity, acceleration and dynamic trajectory of the target. Experiments show that this method has a good tracking effect on the target tracking in the video which is partially occluded during the motion.
VL - 7
IS - 2
ER -

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Author Information

Dang Kexin

School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China
Zhang Xiongfei

School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China
Chen Zhihong

School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China
Yang Ziwen

School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China
Li Chen

School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China

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Plain Text BibTeX RIS

APA Style

Dang Kexin, Zhang Xiongfei, Chen Zhihong, Yang Ziwen, Li Chen. (2019). An Anti-occlusion Video Target Tracking Method Based on Kalman Filter. Journal of Electrical and Electronic Engineering, 7(2), 69-74. https://doi.org/10.11648/j.jeee.20190702.17

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ACS Style

Dang Kexin; Zhang Xiongfei; Chen Zhihong; Yang Ziwen; Li Chen. An Anti-occlusion Video Target Tracking Method Based on Kalman Filter. J. Electr. Electron. Eng. 2019, 7(2), 69-74. doi: 10.11648/j.jeee.20190702.17

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AMA Style

Dang Kexin, Zhang Xiongfei, Chen Zhihong, Yang Ziwen, Li Chen. An Anti-occlusion Video Target Tracking Method Based on Kalman Filter. J Electr Electron Eng. 2019;7(2):69-74. doi: 10.11648/j.jeee.20190702.17

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@article{10.11648/j.jeee.20190702.17,
  author = {Dang Kexin and Zhang Xiongfei and Chen Zhihong and Yang Ziwen and Li Chen},
  title = {An Anti-occlusion Video Target Tracking Method Based on Kalman Filter},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {7},
  number = {2},
  pages = {69-74},
  doi = {10.11648/j.jeee.20190702.17},
  url = {https://doi.org/10.11648/j.jeee.20190702.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20190702.17},
  abstract = {The human visual system is the main component of the brain-based information processing system. It is the main way for humans to obtain external information. Therefore, the emerging science represented by computer vision came into being. Video-specific target tracking is a core issue in the field of computer vision research. It has been widely studied and concerned, and it has been widely used in many fields, such as video surveillance, intelligent navigation, medical diagnosis, augmented reality and virtual reality, etc. The specific moving target tracking algorithm and improved algorithm in the video are studied to some extent. Combining the meanshift algorithm with Kalman filtering can solve the occlusion problem of moving targets in complex scenes. This project intends to use Kalman filter and meanshift algorithm to detect and track the specified target in the video image sequence, and obtain the position, angle, scale, velocity, acceleration and dynamic trajectory of the target. Experiments show that this method has a good tracking effect on the target tracking in the video which is partially occluded during the motion.},
 year = {2019}
}

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