ACM Transactions on Graphics 2013(Proceedings of SIGGRAPH 2013) 

Hui Huang^{1}
Shihao Wu^{ 1,2} Daniel CohenOr^{3}
Minglun Gong^{4} Hao Zhang^{5}
Guiqing Li^{2 } Baoquan Chen^{1} 



AbstractWe introduce L1medial skeleton as a curve skeleton representation for 3D point cloud data. The L1median is wellknown as a robust global center of an arbitrary set of points. We make the key obser vation that adapting L1medians locally to a point set representing a 3D shape gives rise to a onedimensional structure, which can be seen as the localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L1medial skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with signiﬁcant noise, outliers, and large areas of missing data. We demonstrate L1medial skeletons extracted from raw scans of a variety of shapes, including those modeling highgenus 3D objects, plants, and curve networks.


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Overview 

Figure 2: Overview of L1medial skeleton extraction. Given an incomplete and noisy raw scan (b) of the object in (a), we randomly select a subset of samples, shown in red in (c). These points are iteratively projected onto a skeletal point cloud with a gradually increasing neighborhood size (dg). After downsampling, smoothing, and recentering, the ﬁnal curve skeleton is obtained (h).


Results 

Figure 3: Results gallery in the paper.


Comparison 

Figure 4: Comparing ROSA skeletons (c) from [Tagliasacchi et al. 2009] with our L1medial skeletons (d) extracted from a set of raw scans (b). Blue boxes emphasize where the errors (small or big) occur. Note that ROSA requires correct normal estimation on each input.


AcknowledgementsThe authors would like to thank all the reviewers for their valuable comments. The raw scan data shown in Figure 8 is courtesy of Andrea Tagliasacchi. This work is supported in part by grants from NSFC (61103166, 61232011, 61025012), Guangdong Science and Technology Program (2011B050200007), Shenzhen Innovation Program (CXB201104220029A and ZD201111080115A), Shenzhen Nanshan Program (KC2012JSJS0019A), Natural Science and Engineering Research Council of Canada (293127 and 611370) and the Israel Science Foundation. 

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