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首页> 外文会议>2016 IEEE International Conference on Signal and Image Processing >Feature preserving holes filling of scattered point cloud based on tensor voting
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Feature preserving holes filling of scattered point cloud based on tensor voting

机译：基于张量投票的零散点云特征保留孔填充

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摘要

This paper presented a novel holes filling method for the scattered point cloud, particularly for recovering the missing points at featured curves or corners. Firstly, hole-boundary point and feature point were extracted to determine the incomplete feature curves. According to these two point sets, the holes were categorized into two types, featured holes and non-featured holes. Secondly, tensor voting was used to restore the missing feature points of the incomplete feature curves. Accordingly, original holes were divided into sub-holes without missing feature. Finally, all the non-featured holes were filled by the tensor voting. Experimental results show that the proposed method could accurately and effectively restore the original shape of the hole including the sharp features.
机译：本文提出了一种用于散布点云的新型孔填充方法，特别是用于恢复特征曲线或拐角处的缺失点。首先，提取孔的边界点和特征点，以确定不完整的特征曲线。根据这两个点集，将孔分为特征孔和非特征孔两种类型。其次，使用张量投票来恢复不完整特征曲线的缺失特征点。因此，原始孔被划分为子孔而没有缺失特征。最后，所有未完成的漏洞都由张量投票填补。实验结果表明，所提出的方法能够准确有效地恢复包括尖锐特征的孔的原始形状。

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