Low-density point eating algorithm for surface reconstruction from dense scans

Shi Bao-Quan; Feng Xiao-Yuan; Zhang Li-Kun; Yao Chen-Song; Ye Jun-Jie

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Low-density point eating algorithm for surface reconstruction from dense scans

机译：密度扫描表面重建的低密度点饮食算法

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We present a low-density point eating algorithm for surface reconstruction from dense scans. First, the density map for each scan is estimated and the boundary densities are down-weighted. Subsequently, the poorly scanned low-density overlapping points are eaten up based on a user-specified threshold. Finally, the overlapping areas are thinned by using the moving least-squares operator and the homogeneous points are weighted averaged. The new algorithm can extract smooth but detailed point set surfaces that are as close as possible to the ground truth. The good performance of the new algorithm is demonstrated by comparison with several advanced surface reconstruction algorithms. (C) 2018 Optical Society of America

机译：我们介绍了一种低密度点饮食算法，用于致密扫描的表面重建。首先，估计每个扫描的密度图，边界密度被缩小。随后，基于用户指定的阈值，扫描差的低密度重叠点差。最后，通过使用移动最小二乘算子来减薄重叠区域，并且均匀点是加权平均。新算法可以提取光滑但详细的点设置表面，尽可能接近地面。通过与多个先进的表面重建算法进行比较，证明了新算法的良好性能。（c）2018年光学学会

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来源
《Applied optics》 |2018年第8期|共12页
作者
Shi Bao-Quan; Feng Xiao-Yuan; Zhang Li-Kun; Yao Chen-Song; Ye Jun-Jie;
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Xidian Univ Minist Educ Key Lab Elect Equipment Struct Design Xian 710071 Shaanxi Peoples R China;

Xidian Univ Minist Educ Key Lab Elect Equipment Struct Design Xian 710071 Shaanxi Peoples R China;

Xidian Univ Minist Educ Key Lab Elect Equipment Struct Design Xian 710071 Shaanxi Peoples R China;

Xidian Univ Minist Educ Key Lab Elect Equipment Struct Design Xian 710071 Shaanxi Peoples R China;

Xidian Univ Minist Educ Key Lab Elect Equipment Struct Design Xian 710071 Shaanxi Peoples R China;

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正文语种 eng
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Low-density point eating algorithm for surface reconstruction from dense scans

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