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Joint estimation-segmentation of optic flow

机译:光流的联合估计-分段

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In this paper we address the intricate issue of jointly recovering the apparent velocity field hetween two consecutive frames and its underlying partition. We design a global cost functional including robust estimators. These estimators enable to deal with the large deviations occurring in the different energy terms and offer the possibility to introduce a simple coupling between a dense optical flow field and a segmentation. This coupling is also reinforced by a parametric likeness term. The resulting estimation-segmentation model thus involves a tight cooperation between a local estimation process and a global modelization. The minimization of the final cost function is conducted efficiently by a multigrid optimization algorithm.
机译:在本文中,我们解决了联合恢复两个连续帧及其下层分区之间的视在速度场的复杂问题。我们设计了一个包含强大估计量的全局成本函数。这些估计器能够处理在不同能量项中出现的大偏差,并提供了在密集的光流场和分段之间引入简单耦合的可能性。通过参数相似项也可以增强这种耦合。因此,所得的估计分段模型涉及局部估计过程与全局建模之间的紧密协作。最终成本函数的最小化通过多网格优化算法有效地进行。

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