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Registration method for scattered cloud data based on feature points

机译:基于特征点的分散云数据注册方法

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摘要

Registration of scattered cloud data is an important topic in model construction. Firstly, local geometric characteristic of point clouds is expressed by point feature. Then, coarse registration is implemented based on feature points selected. By reducing search scope of matching points and accelerating search speed based on k-d tree, the conventional ICP algorithm is improved. Experiment results show that it is valid.
机译:分散云数据的注册是模型构建中的重要主题。首先,用点特征表示点云的局部几何特征。然后,基于选择的特征点实现粗注册。通过减小匹配点的搜索范围并基于k-d树加快搜索速度,改进了传统的ICP算法。实验结果表明是有效的。

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