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ment Fund (ERDF).
REFERENCES
Bazazian, D., Casas, J., and Ruiz-Hidalgo, J. (2015).
Fast and robust edge extraction in unorganized point
clouds. Digital Image Computing: Techniques and
Applications (DICTA).
Choi, C., Trevor, A. J. B., and Christensen, H. I. (2013).
RGB-D edge detection and edge-based registration. In
2013 IEEE/RSJ International Conference on Intelli-
gent Robots and Systems (IROS), pages 1568–1575.
Daniels, J., Ochotta, T., and Ha, L. (2008). Spline-based
feature curves from pointsampled geometry. Vis.
Comput, 26(6):449–462.
Demarsin, K., Vanderstraeten, D., Volodine, T., and Roose,
D. (2007). Detection of closed sharp edges in point
clouds using normal estimation and graph theory.
Computer-Aided Design, 39(4):276–283.
Feng, C., Taguchi, Y., and Kamat, V. (2014). Fast plane
extraction in organized point clouds using agglomera-
tive hierarchical clustering. IEEE International Con-
ference on Robotics and Automation (ICRA), pages
6218–6225.
Fleischman, S., Cohenor, D., and Silva, T. (2005). Robust
moving least-squares fitting with sharp features. ACM
Trans Graph, pages 37–49.
Gross, M. and Pfister, H. (2007). Point-based graphics (the
morgan kaufmann series in computer graphics). San
Francisco, CA, USA: Morgan Kaufmann Publishers.
Gumhold, S., Wang, X., and Mcleod, R. (2001). Feature
extraction from point clouds. Proceedings of 10th In-
ternational Meshing Roundtable.
Hackel, T., Wegner, J. D., and Schindler, K. (2016). Con-
tour detection in unstructured 3d point clouds. In
CVPR 2016, volume 3, Las Vegas, NV, US.
Ho, H. and Gibbines, D. (2009). Curvature-based approach
for multi-scale feature extraction from 3d meshes and
unstructured point clouds. IET Computer Vision,
3(4):201–212.
Hoppe, H., Derose, T., Duchamp, T., McDonald, J., and
Stuetzle, W. (1992). Surface reconstruction from un-
organized points. In: ACM Siggraph, page 7178.
Ioannou, Y., Taati, B., Harrap, R., and Greenspan, M.
(2015). Difference of normals as a multi-scale op-
erator in unorganized point clouds. 3D Imaging,
Modeling, Processing, Visualization and Transmis-
sion (3DIMPVT), pages 501–508.
Kustra, J., Jalba, A., and Telea, A. (2014). Robust segmen-
tation of multiple intersecting manifolds from unori-
ented noisy point clouds. Computer Graphics Forum,
33(1):73–87.
Lange, C. and K., P. (2005). Anisotropic smoothing of point
sets. Comput Aided Geom Des, 22(7):680692.
Lin, Y., Wang, C., Cheng, J., Chen, B., Jia, C., Chen, Z.,
and Li, J. (2015). Line segment extraction for large
scale unorganized point clouds. ISPRS Journal of
Photogrammetry and Remote Sensing, 102:172–183.
Liu, Y. and Youlun, X. (2008). Automatic segmentation of
unorganized noisy point clouds based on the gaussian
map. Computer-Aided Design, 40(5):576–594.
Mitra, N. and Nguyen, A. (2003). Estimating surface nor-
mals in noisy point cloud data. Proceedings of the
nineteenth annual symposium on computational ge-
ometry, pages 322–328.
Oztireli, C., Guennebaud, G., and Gross, M. (2009). Fea-
ture preserving point set surfaces based on non-linear
kernel regression. Computer Graphics Forum, 28(2).
Park, M., Lee, S., and Lee, K. (2012). Multi-scale tensor
voting for feature extraction from unstructured point
clouds. Graphical Models, 74(4):197–208.
Pauly, M., Keiser, R., and Gross, M. (2003a). Multi-scale
feature extraction on pointsampled surfaces. Com-
puter Graphics Forum, 22(3):281–289.
Pauly, M., Keiser, R., Kobbelt, L., and Gross, M. (2003b).
Shape modeling with point-sampled geometry. ACM
Trans Graph, 22(3):641650.
Rabbani, T., van Den Heuvel, F., and Vosselmann, G.
(2006). Segmentation of point clouds using smooth-
ness constraint. Int. Arch. Photogramm. Remote. Sens.
Spat. Inf. Sci., 36:248–253.
Reisner-Kollmann, I. and Maierhofer, S. (2012). Segment-
ing multiple range images with primitive shapes. 19th
Int. Conf. on Systems, Signals and Image Processing.
Rieck, B. and Leitte, H. (2014). Structural analysis of multi-
variate point clouds using simplicial chains. Computer
Graphics Forum, 33(8).
Sidiropoulos, A. A. and Lakakis, K. N. (2016). Edge Points
Detection in Unorganized Point Clouds. Int. J. Con-
structive Research in Civil Engineering, 2(3):8 – 15.
Son, H. and Kim, C. (2013). Fully automated as-built 3d
pipeline segmentation based on curvature computa-
tion from laser-scanned data. Computing in Civil En-
gineering, pages 765–772.
Wang, Y. and Feng, H. (2015). Outlier detection for scanned
point clouds using majority voting. Computer-Aided
Design, 62:31–43.
Weber, C., Hahmann, S., and Hagen, H. (2010). Methods
for feature detection in point clouds. Visualization of
Large and Unstructured Data Sets IRTG Workshop,
pages 90–99.
Weber, C., Hahmann, S., Hagen, H., and Bonneau, G.
(2012). Sharp feature preserving mls surface recon-
struction based on local feature line approximations.
Graphical Models, 74(6):335–345.
Xu, J., Zhou, M., Wu, Z., Shui, W., and Ali, S. (2015). Ro-
bust surface segmentation and edge feature lines ex-
traction from fractured fragments of relics. Journal of
Computational Design and Engineering, 2(2):79–87.
Zhang, G., Vela, P., and Brilakis, I. (2013). Detecting, fit-
ting, and classifying surface primitives for infrastruc-
ture point cloud data. ASCE Computing in Civil Engi-
neering, pages 589–596.
Segmentation-based Multi-scale Edge Extraction to Measure the Persistence of Features in Unorganized Point Clouds
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