A Fractional Order Total Variation Model for the Estimation of Optical Flow

被引:0
|
作者
Kumar, Pushpendra [1 ]
Kumar, Sanjeev [1 ]
Balasubramanian, R. [2 ]
机构
[1] IIT Roorkee, Dept Math, Roorkee 247667, Uttar Pradesh, India
[2] IIT Roorkee, Dept Comp Sci & Engn, Roorkee 247667, Uttar Pradesh, India
来源
2015 FIFTH NATIONAL CONFERENCE ON COMPUTER VISION, PATTERN RECOGNITION, IMAGE PROCESSING AND GRAPHICS (NCVPRIPG) | 2015年
关键词
Fractional derivative; Image sequence; Optical flow; Total variation regularization; FIELDS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a fractional order total variation (TV) model is presented for estimating the optical flow in the image sequences. The proposed fractional order model is introduced by generalizing a variational flow model formed with a quadratic and a total variation terms. However, it is difficult to solve this generalized model due to the non-differentiability of the total variation regularization term. The Grunwald-Letnikov derivative is used to discretize the fractional order derivative. The resulting formulation is solved by using an efficient numerical algorithm. The experimental results verify that the proposed model yields a dense flow and preserves discontinuities in the flow field. Moreover, It also provides a significant robustness against outliers.
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页数:4
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