Regularized Patch Motion Estimation

I. Patras, M. Worring
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引用次数: 2

Abstract

This paper presents a new formulation of the problem of motion estimation which attempts to give solutions to classical problems in the field, such as detection of motion discontinuities and insufficiency of the optical flow constraint in areas with low intensity variation. An initial intensity segmentation phase partitions each frame into patches so that areas with low intensity variation are guaranteed to belong to the same patch. A parametric model is assumedto describe the motion of each patch. Regularization in the motion parameter space provides the additional constraints for patches where the intensity variation is insufficient to constrain the estimation of the motion parameters and smooths the corresponding motion field. In orderto preserve motion discontinuities we use robust functions as a regularization mean. Experimental results show that the proposed method deals successfully with motions large in magnitude, motion discontinuities and produces accurate piecewise smooth motion fields.
正则化Patch运动估计
本文提出了运动估计问题的一个新公式,试图解决运动估计领域的经典问题,如运动不连续的检测和光流约束在低强度变化区域的不足。初始强度分割阶段将每帧图像分割成小块,以保证强度变化小的区域属于同一个小块。假设一个参数模型来描述每个小块的运动。运动参数空间的正则化为强度变化不足以约束运动参数估计的斑块提供了额外的约束,并平滑了相应的运动场。为了保持运动不连续,我们使用鲁棒函数作为正则化均值。实验结果表明,该方法能有效地处理大幅度运动和运动不连续的情况,并能得到精确的分段平滑运动场。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
3.70
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0.00%
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