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首页> 外文会议>Nanophotonics Australasia 2017 >The registration of non-cooperative moving targets laser point cloud in different view point
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The registration of non-cooperative moving targets laser point cloud in different view point

机译：非合作移动目标激光点云在不同视点的配准

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Non-cooperative moving target multi-view cloud registration is the key technology of 3D reconstruction of laser three-dimension imaging. The main problem is that the density changes greatly and noise exists under different acquisition conditions of point cloud. In this paper, firstly, the feature descriptor is used to find the most similar point cloud, and then based on the registration algorithm of region segmentation, the geometric structure of the point is extracted by the geometric similarity between point and point, The point cloud is divided into regions based on spectral clustering, feature descriptors are created for each region, searching to find the most similar regions in the most similar point of view cloud, and then aligning the pair of point clouds by aligning their minimum bounding boxes. Repeat the above steps again until registration of all point clouds is completed. Experiments show that this method is insensitive to the density of point clouds and performs well on the noise of laser three-dimension imaging.
机译：非合作移动目标多视角云配准是激光三维成像3D重建的关键技术。主要问题是在不同的点云采集条件下，密度变化很大，存在噪声。本文首先利用特征描述符找到最相似的点云，然后基于区域分割的配准算法，通过点与点之间的几何相似度提取出点的几何结构。根据频谱聚类将其划分为多个区域，为每个区域创建特征描述符，在最相似的视角云中搜索以找到最相似的区域，然后通过对齐其最小边界框来对齐一对点云。再次重复上述步骤，直到所有点云的配准完成。实验表明，该方法对点云密度不敏感，对激光三维成像的噪声效果良好。

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