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A segmentation method based on motion from image sequence and depth

机译:基于图像序列和深度的运动分割方法

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The author proposes a segmentation method based on the gradient method for multiple moving objects which may include an object for which a unique interpretation of the motion is difficult. By the gradient method, the 3-D motion parameters of a rigid object can be estimated without determining correspondence as a pseudoinverse solution for a system of linear equations if the 3-D structure of the object is already given. Based on the residual square-error in the motion estimation, the image is segmented if it contains regions with different motions. If the motions are recognized as the same, the regions are merged. Thus, the object is extracted by iterating the segmentation and merge on the image.
机译:作者提出了一种基于梯度法的分割方法,用于多个运动物体,其中可能包括难以对运动进行唯一解释的物体。通过梯度法,如果已经给出物体的3D结构,则可以在不将刚性物体的3D运动参数确定为线性方程组的拟逆解的情况下估计出刚性物体的3D运动参数。基于运动估计中的残留平方误差,如果图像包含具有不同运动的区域,则对图像进行分割。如果识别出的运动相同,则合并区域。因此,通过迭代分割来提取对象并在图像上合并。

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