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An Improved Fractional-Order Variational Optical Flow Model Combining Structure Tensor
Author(s) -
Bin Zhu,
Zhaodong Wang,
Lianfang Tian,
Jinmei Guo,
Ling-Jian Wang,
Jameel Ahmed Bhutto
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/9960784
Subject(s) - optical flow , smoothness , structure tensor , flow (mathematics) , constraint (computer aided design) , mathematics , brightness , tensor (intrinsic definition) , computer vision , geometric flow , algorithm , artificial intelligence , computer science , image (mathematics) , mathematical analysis , physics , optics , geometry
Dealing with problems of illumination changes in optical flow estimation, an improved variational optical flow model is proposed in this paper. The local structure constancy constraint (LSCC) is applied in the data term of the traditional HS (Horn & Schunck) optical flow model to substitute the brightness constancy constraint. The fractional-order smoothness constraint (FSC) is applied in the smoothness term of the HS model. Then, the detailed calculation processes from the optical flow model to the optical flow value are explained. The structure tensor in LSCC is an image feature that is constant in the illumination changes scene. The fractional differential coefficient in FSC can fuse the local neighborhood optical flow vector into the optical flow vector of the target pixel, which can improve the integrity of the motion region with the same motion speed. Combining LSCC with FSC, our improved optical flow model can obtain an accurate optical flow field with clear outline in the illumination abnormity scene. The experimental results show that, compared with other optical flow models, our model is more suitable for the illumination changes scene and can be employed in outdoor motion detection projects.

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