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Adaptive Segmentation Method Based on Similarity of Laser Point Cloud Topology

机译:基于激光点云拓扑相似度的自适应分割方法

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Laser point cloud segmentation is the basis of target splicing or recognition. In this paper, a point cloud segmentation method based on point topology is proposed. The relationship between neighboring points is obtained by the curvature relationship between points. The relationship within point cloud between each point is established, and then the point cloud is divided by cutting the graph. The feature of eigenvalue of the Laplacian matrix realizes the adaptive segmentation. Three different kind of point cloud are tested with the algorithm in this paper and the result show that the algorithm has good performance on point cloud cutting of obvious characteristics and robust to noise.
机译:激光点云分割是目标拼接或识别的基础。提出了一种基于点拓扑的点云分割方法。通过点之间的曲率关系获得相邻点之间的关系。建立每个点之间的点云内的关系,然后通过切割图形对点云进行划分。拉普拉斯矩阵特征值的特征实现了自适应分割。用该算法对三种不同类型的点云进行了测试,结果表明该算法在点云切割方面具有良好的性能,具有明显的特征和抗噪声能力。

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