A 3D Motion Vector Database for Dynamic Point Clouds
A 3D Motion Vector Database for Dynamic Point Clouds
复制标题
动态点云的 3D 运动矢量数据库
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Camilo C. Dorea
中科院分区：
文献类型：
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作者：
André Souto;R. Queiroz;Camilo C. Dorea
由于点云所代表的大量数据以及连续帧的几何差异，为整个点云数据集生成运动向量可能需要大量的时间和计算资源。考虑到这一点，我们为两个流行的动态点云数据集的所有帧提供了一个3D运动矢量数据库。运动矢量是通过平移运动估计过程获得的，该过程将点云划分为维度为M×M×M的块，并对每个块估计一个运动矢量。我们的数据库包含M=8和M=16的运动矢量。这项工作的目标是描述这个公开可用的3D运动矢量数据库，它可以用于不同的目的，例如压缩动态点云。
Due to the large amount of data that point clouds represent and the differences in geometry of successive frames, the generation of motion vectors for an entire point cloud dataset may require a significant amount of time and computational resources. With that in mind, we provide a 3D motion vector database for all frames of two popular dynamic point cloud datasets. The motion vectors were obtained through translational motion estimation procedure that partitions the point clouds into blocks of dimensions M x M x M , and for each block, a motion vector is estimated. Our database contains motion vectors for M = 8 and M = 16. The goal of this work is to describe this publicly available 3D motion vector database that can be used for different purposes, such as compression of dynamic point clouds.