极地研究

极地研究

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Auroral event detection using spatiotemporal statistics of local motion vectors

WANG Qian1,2*, LIANG Jimin3 & HU Zejun2   

  1. 1 Image and Information Processing Research Center, Xi’an University of Posts and Telecommunications, Xi’an 710121,
    China;
    2 SOA Key Laboratory for Polar Science, Polar Research Institute of China, Shanghai 200136, China;
    3 Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi’an 710071, China
  • 出版日期:1963-09-30 发布日期:1963-09-30
  • 通讯作者: WANG Qian

Auroral event detection using spatiotemporal statistics of local motion vectors

WANG Qian1,2*, LIANG Jimin3 & HU Zejun2   

  1. 1 Image and Information Processing Research Center, Xi’an University of Posts and Telecommunications, Xi’an 710121,
    China;
    2 SOA Key Laboratory for Polar Science, Polar Research Institute of China, Shanghai 200136, China;
    3 Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi’an 710071, China
  • Online:1963-09-30 Published:1963-09-30
  • Contact: WANG Qian

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摘要： The analysis and exploration of auroral dynamics are very significant for studying auroral mechanisms. This paper proposes a method based on auroral dynamic processes for detecting auroral events automatically. We first obtained the motion fields using the multiscale fluid flow estimator. Then, the auroral video frame sequence was represented by the spatiotemporal statistics of local motion vectors. Finally, automatic auroral event detection was achieved. The experimental results show that our methods could detect the required auroral events effectively and accurately, and that the detections were independent on any specific auroral event. The proposed method makes it feasible to statistically analyze a large number of continuous observations based on the auroral dynamic process.

关键词: automatic detection, auroral event, fluid flow

Abstract: The analysis and exploration of auroral dynamics are very significant for studying auroral mechanisms. This paper proposes a method based on auroral dynamic processes for detecting auroral events automatically. We first obtained the motion fields using the multiscale fluid flow estimator. Then, the auroral video frame sequence was represented by the spatiotemporal statistics of local motion vectors. Finally, automatic auroral event detection was achieved. The experimental results show that our methods could detect the required auroral events effectively and accurately, and that the detections were independent on any specific auroral event. The proposed method makes it feasible to statistically analyze a large number of continuous observations based on the auroral dynamic process.

Key words: automatic detection, auroral event, fluid flow