GNSS World of China

Volume 44 Issue 3
Jun.  2019
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CUI Jialiang, FENG Zhaohui, LI Qin, ZHAO Hongying. CNN and RNN-based pixel-wise video object tracking algorithm[J]. GNSS World of China, 2019, 44(3): 1-6. doi: DOI:10.13442/j.gnss.1008-9268.2019.03.001
Citation: CUI Jialiang, FENG Zhaohui, LI Qin, ZHAO Hongying. CNN and RNN-based pixel-wise video object tracking algorithm[J]. GNSS World of China, 2019, 44(3): 1-6. doi: DOI:10.13442/j.gnss.1008-9268.2019.03.001
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CNN and RNN-based pixel-wise video object tracking algorithm

doi: DOI:10.13442/j.gnss.1008-9268.2019.03.001

  • School of Earth and Space Sciences, Peking University,Beijing100871,China

  • Publish Date: 2019-06-15
    Abstract
  • Video object tracking is a research hotpot of computer vision, but the object tracking algorithm is one of weaknesses in localization with video. In this paper, we introduced the pixel-wise video object tracking problem. We proposed a pixel-wise video object tracking algorithm based on convolution and recurrent neural network of deep learning technology and the latest research results in image segmentation to solve the problem. By designed and conducted an experiment and evaluation on a public dataset, the algorithm shows abilities on obtaining the boundary of objects in videos.

     

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