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Joint optical flow estimation, segmentation, and 3D interpretation with level sets

机译:带有水平集的联合光流估计,分段和3D解释

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This paper describes a variational method with active curve evolution and level sets for the estimation, segmentation, and 3D interpretation of optical flow generated by independently moving rigid objects in space. Estimation, segmentation, and 3D interpretation are performed jointly. Segmentation is based on an estimate of optical flow consistent with a single rigid motion in each segmentation region. The method, which allows both viewing system and viewed objects to move, results in three steps iterated until convergence: (a) evolution of closed curves via level sets and, in each region of the segmentation, (b) linear least squares computation of the essential parameters of rigid motion, (c) estimation of optical flow consistent with a single rigid motion. The translational and rotational components of rigid motion and regularized relative depth are recovered analytically for each region of the segmentation from the estimated essential parameters and optical flow. Several examples with real image sequences are provided which verify the validity of the method. (c) 2005 Elsevier Inc. All rights reserved.
机译:本文介绍了一种具有主动曲线演化和能级集的变分方法,用于估计,分割和3D解释由空间中独立移动的刚性物体产生的光流。估计,分割和3D解释共同执行。分割基于与每个分割区域中单个刚性运动一致的光流估计。该方法允许观察系统和被观察对象都移动,导致三个步骤重复进行直到收敛:(a)通过水平集演化闭合曲线,在分割的每个区域中,(b)计算线性最小二乘刚性运动的基本参数,(c)估计与单个刚性运动一致的光流。从估计的基本参数和光流中,针对分割的每个区域,解析性地恢复了刚性运动和规则化相对深度的平移和旋转分量。提供了带有真实图像序列的几个示例,验证了该方法的有效性。 (c)2005 Elsevier Inc.保留所有权利。

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