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RPBS: Rotational Projected Binary Structure for Point Cloud Representation

机译：RPBS：用于点云表示的旋转投影二进制结构

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In this paper, we proposed a novel three-dimension local surface descriptor named RPBS for point cloud representation. First, points cropped form the query point within a predefined radius is regard as a local surface patch. Then pose normalization is done to the local surface to equip our descriptor with the invariance to rotation transformation. To obtain more information about the cropped surface, multi-view representation is formed by successively rotating it along the coordinate axis. Further, orthogonal projections to the three coordinate plane are adopted to construct two-dimension distribution matrixes, and binarization is applied to each matrix by following the rule that whether the grid is occupied, if yes, set the grid one, otherwise zero. We calculate the binary maps from all the viewpoints and concatenate them together as the final descriptor. Comparative experiments for evaluating our proposed descriptor is conducted on the standard dataset named Bologna with several state-of-the-art 3D descriptors, and results show that our descriptor achieves the best performance on feature matching experiments.
机译：在本文中，我们提出了一种新颖的三维局部表面描述符RPBS，用于点云表示。首先，将在预定半径范围内从查询点裁剪的点视为局部曲面补丁。然后对局部表面进行姿势归一化，以使我们的描述符具有旋转变换的不变性。为了获得有关裁剪表面的更多信息，可通过沿坐标轴连续旋转多视图来形成多视图表示。此外，采用正交于三个坐标平面的投影来构造二维分布矩阵，并通过遵循是否占据网格的规则对每个矩阵进行二值化，如果是，则将网格设置为1，否则设置为零。我们从所有视点计算二进制映射，并将它们连接在一起作为最终描述符。在名为Bologna的标准数据集上使用几个最新的3D描述符进行了评估我们提出的描述符的比较实验，结果表明，我们的描述符在特征匹配实验中达到了最佳性能。

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