ZHENG Hong, HUANG Ying, LING Haibin, ZOU Qi, YANG Hao. Accurate Segmentation for Infrared Flying Bird Tracking[J]. Chinese Journal of Electronics, 2016, 25(4): 625-631. doi: 10.1049/cje.2016.07.008
Citation: ZHENG Hong, HUANG Ying, LING Haibin, ZOU Qi, YANG Hao. Accurate Segmentation for Infrared Flying Bird Tracking[J]. Chinese Journal of Electronics, 2016, 25(4): 625-631. doi: 10.1049/cje.2016.07.008

Accurate Segmentation for Infrared Flying Bird Tracking

doi: 10.1049/cje.2016.07.008
Funds:  This work is partly supported by the Beijing Higher Education Young Elite Teacher Project (No.YETP0546).
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  • Corresponding author: HUANG Ying (corresponding author) received the Ph.D. degree from the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China, in 2016. He was a visiting student with Temple University, Philadelphia, PA, USA, in 2014. His research interests include computer vision and machine learning. (Email:yw155@buaa.edu.cn)
  • Received Date: 2015-09-01
  • Rev Recd Date: 2016-03-23
  • Publish Date: 2016-07-10
  • Bird strikes present a huge risk for air vehicles, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation. For improving the effectiveness and efficiency of bird monitoring, computer vision techniques have been proposed to detect birds, determine bird flying trajectories, and predict aircraft takeoff delays. Flying bird with a huge deformation causes a great challenge to current tracking algorithms. We propose a segmentation based approach to enable tracking can adapt to the varying shape of bird. The approach works by segmenting object at a region of interest, where is determined by the object localization method and heuristic edge information. The segmentation is performed by Markov random field, which is trained by foreground and background mixture Gaussian models. Experiments demonstrate that the proposed approach provides the ability to handle large deformations and outperforms the most state-of-the-art tracker in the infrared flying bird tracking problem.
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