Three-dimensional motion estimation via matrix completion.

Kun Li, Qionghai Dai, Wenli Xu, Jingyu Yang, Jianmin Jiang
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引用次数: 17

Abstract

Three-dimensional motion estimation from multiview video sequences is of vital importance to achieve high-quality dynamic scene reconstruction. In this paper, we propose a new 3-D motion estimation method based on matrix completion. Taking a reconstructed 3-D mesh as the underlying scene representation, this method automatically estimates motions of 3-D objects. A "separating + merging" framework is introduced to multiview 3-D motion estimation. In the separating step, initial motions are first estimated for each view with a neighboring view. Then, in the merging step, the motions obtained by each view are merged together and optimized by low-rank matrix completion method. The most accurate motion estimation for each vertex in the recovered matrix is further selected by three spatiotemporal criteria. Experimental results on data sets with synthetic motions and real motions show that our method can reliably estimate 3-D motions.

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三维运动估计通过矩阵完成。
多视点视频序列的三维运动估计是实现高质量动态场景重建的关键。本文提出了一种新的基于矩阵补全的三维运动估计方法。该方法以重建的三维网格作为底层场景表示,自动估计三维物体的运动。将“分离+合并”框架引入到多视图三维运动估计中。在分离步骤中,首先对具有相邻视图的每个视图估计初始运动。然后,在合并步骤中,将每个视图得到的运动合并在一起,并采用低秩矩阵补全方法进行优化。通过三个时空准则对恢复矩阵中每个顶点进行最精确的运动估计。在合成运动和真实运动数据集上的实验结果表明,该方法可以可靠地估计三维运动。
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