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Concurrent 3-D motion segmentation and 3-D interpretation of temporal sequences of monocular images

机译:并发3-D运动分割和单眼图像时间序列的3-D解释

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The purpose of this study is to investigate a variational method for joint multiregion three-dimensional (3-D) motion segmentation and 3-D interpretation of temporal sequences of monocular images. Interpretation consists of dense recovery of 3-D structure and motion from the image sequence spatiotemporal variations due to short-range image motion. The method is direct insomuch as it does not require prior computation of image motion. It allows movement of both viewing system and multiple independently moving objects. The problem is formulated following a variational statement with a functional containing three terms. One term measures the conformity of the interpretation within each region of 3-D motion segmentation to the image sequence spatiotemporal variations. The second term is of regularization of depth. The assumption that environmental objects are rigid accounts automatically for the regularity of 3-D motion within each region of segmentation. The third and last term is for the regularity of segmentation boundaries. Minimization of the functional follows the corresponding Euler-Lagrange equations. This results in iterated concurrent computation of 3-D motion segmentation by curve evolution, depth by gradient descent, and 3-D motion by least squares within each region of segmentation. Curve evolution is implemented via level sets for topology independence and numerical stability. This algorithm and its implementation are verified on synthetic and real image sequences. Viewers presented with anaglyphs of stereoscopic images constructed from the algorithm's output reported a strong perception of depth.
机译:这项研究的目的是研究一种变分方法,用于联合多区域三维(3-D)运动分割和单眼图像的时间序列的3-D解释。解释包括3-D结构的密集恢复以及由于短距离图像运动而引起的图像序列时空变化引起的运动。该方法是直接的,因为它不需要图像运动的事先计算。它允许同时移动查看系统和多个独立移动的对象。该问题是根据包含三个项的函数的变式陈述来表述的。一个术语测量3-D运动分割的每个区域内解释与图像序列时空变化的一致性。第二项是深度的正则化。环境物体是刚性的假设自动解释了每个分割区域内3D运动的规律性。第三项也是最后一项是关于分割边界的规律性。泛函的最小化遵循相应的Euler-Lagrange方程。这将导致在分割的每个区域内通过曲线演化,深度通过梯度下降以及3-D运动通过最小二乘法进行迭代并发计算。曲线演化是通过级别集实现的,以实现拓扑独立性和数值稳定性。该算法及其实现在合成和真实图像序列上得到了验证。观看者展示了根据算法输出构造的立体图像的立体图,他们对深度感很强。

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