Edge Detection and Feature Line Tracing in 3D-Point Clouds by Analyzing Geometric Properties of Neighborhoods

Remote Sensing - Tập 8 Số 9 - Trang 710
Huan Ni1, Xiangguo Lin2, Xiaogang Ning2, Jixian Zhang1
1School of Resource and Environmental Sciences, Wuhan University, No. 129 Luoyu Road, Wuhan 430079, China
2Chinese Academy of Surveying and Mapping, No. 28 Lianhuachixi Road, Beijing 100830, China

Tóm tắt

This paper presents an automated and effective method for detecting 3D edges and tracing feature lines from 3D-point clouds. This method is named Analysis of Geometric Properties of Neighborhoods (AGPN), and it includes two main steps: edge detection and feature line tracing. In the edge detection step, AGPN analyzes geometric properties of each query point’s neighborhood, and then combines RANdom SAmple Consensus (RANSAC) and angular gap metric to detect edges. In the feature line tracing step, feature lines are traced by a hybrid method based on region growing and model fitting in the detected edges. Our approach is experimentally validated on complex man-made objects and large-scale urban scenes with millions of points. Comparative studies with state-of-the-art methods demonstrate that our method obtains a promising, reliable, and high performance in detecting edges and tracing feature lines in 3D-point clouds. Moreover, AGPN is insensitive to the point density of the input data.

Từ khóa


Tài liệu tham khảo

Ando, 2000, Image field categorization and edge/corner detection from gradient covariance, IEEE Trans. Pattern Anal. Mach. Intell., 2, 179, 10.1109/34.825756

Frei, 1977, Fast boundary detection: A generalization and a new algorithm, IEEE Trans. Comput., 10, 988, 10.1109/TC.1977.1674733

Shanmugam, 1979, An optimal frequency domain filter for edge detection in digital pictures, IEEE Trans. Pattern Anal. Mach. Intell., 1, 37, 10.1109/TPAMI.1979.4766874

McIlhagga, 2011, The Canny edge detector revisited, Int. J. Comput Vision, 91, 251, 10.1007/s11263-010-0392-0

Meer, 2001, Edge detection with embedded confidence, IEEE Trans. Pattern Anal. Mach. Intell., 12, 1351, 10.1109/34.977560

Lin, 2015, Line segment extraction for large scale unorganized point clouds, ISPRS J. Photogramm. Remote Sens., 102, 172, 10.1016/j.isprsjprs.2014.12.027

Guan, 2016, Use of mobile LiDAR in road information inventory: A review, Int. J. Image Data Fusion., 3, 219, 10.1080/19479832.2016.1188860

Zhang, J.X., and Lin, X.G. (2016). Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing. Int. J. Image Data Fusion.

Weinmann, 2015, Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers, ISPRS J. Photogramm. Remote Sens., 105, 286, 10.1016/j.isprsjprs.2015.01.016

Rosenfeld, 1971, Edge and curve detection for visual scene analysis, IEEE Trans. Computers., 20, 562, 10.1109/T-C.1971.223290

Vanderheijden, 1995, Edge and line feature-extraction based on covariance-models, IEEE Trans. Pattern Anal. Mach. Intell., 17, 16, 10.1109/34.368155

Vosselman, 2001, 3D building model reconstruction from point clouds and ground plans, Int. Arch. Photogramm. Remote Sens., 34, 22

Borges, P., Zlot, R., Bosse, M., Nuske, S., and Tews, A. (2010, January 3–7). Vision-based localization using an edge map extracted from 3D laser range data. Proceedings of the International Conference on Robotics and Automation (ICRA), Anchorage, AK, USA.

Demarsin, 2007, Detection of closed sharp edges in point clouds using normal estimation and graph theory, Comput. Aided Des., 39, 276, 10.1016/j.cad.2006.12.005

Sampath, 2010, Segmentation and reconstruction of polyhedral building roofs from aerial lidar point clouds, IEEE Geosci. Remote Sens., 48, 1554, 10.1109/TGRS.2009.2030180

Sampath, A., and Shan, J. (2006, January 1–5). Clustering based planar roof extraction from LiDAR data. Proceedings of the American Society for Photogrammetry Remote Sensing Annual Conference, Reno, NV, USA.

Pu, 2009, Knowledge based reconstruction of building models from terrestrial laser scanning data, ISPRS J. Photogramm. Remote Sens., 64, 575, 10.1016/j.isprsjprs.2009.04.001

Overby, 2004, Automatic 3D building reconstruction from airborne laser scanning and cadastral data using Hough transform, Int. Arch. Photogramm. Remote Sens., 35, 296

Pu, S., and Vosselman, G. (2007, January 12–14). Extracting windows from terrestrial laser scanning. Proceedings of the ISPRS Workshop Laser Scanning and Silvi Laser 2007, Espoo, Finland.

Boulaassal, 2009, Automatic extraction of planar clusters and their contours on building facades recorded by terrestrial laser scanner, Int. J. Archit Comput., 7, 1

Sampath, 2007, Building boundary tracing and regularization from airborne Lidar point clouds, Photogramm. Eng. Remote Sens., 7, 805, 10.14358/PERS.73.7.805

Wang, J., and Shan, J. (2009, January 9–13). Segmentation of LiDAR point clouds for building extraction. Proceedings of the American Society for Photogrammetry Remote Sensing Annual Conference, Baltimore, MD, USA.

Nizar, A., Filin, S., and Doytsher, Y. (2006, January 1–6). Reconstruction of buildings from airborne laser scanning data. Proceedings of the American Society for Photogrammetry Remote Sensing Annual Conference, Reno, NV, USA.

Peternell, 2004, Reconstruction of piecewise planar objects from point clouds, Comput. Aided Des., 36, 333, 10.1016/S0010-4485(03)00102-7

Lafarge, 2012, Creating large-scale city models from 3D-point clouds: A robust approach with hybrid representation, Int. J. Comput. Vision, 1, 69, 10.1007/s11263-012-0517-8

Awrangjeb, 2016, Using point cloud data to identify, trace, and regularize the outlines of buildings, Int. J. Remote. Sens., 3, 551, 10.1080/01431161.2015.1131868

Poullis, 2013, A framework for automatic modeling from point cloud data, IEEE Trans. Pattern Anal. Mach. Intell., 11, 2563, 10.1109/TPAMI.2013.64

Heo, 2013, Productive high-complexity 3D city modeling with point clouds collected from terrestrial LiDAR, Comput. Environ. Urban., 41, 26, 10.1016/j.compenvurbsys.2013.04.002

Rottensteiner, F., and Briese, C. (2003, January 8–10). Automatic generation of building models from LiDAR data and the integration of aerial images. Proceedings of the International Society for Photogrammetry and Remote Sensing, Dresden, Germany.

Alharthy, A., and Bethel, J. (2002, January 9–13). Heuristic filtering and 3d feature extraction from LIDAR data. Proceedings of the ISPRS Commission III, Graz, Austria.

Alharthy, 2004, Detailed building reconstruction from airborne laser data using a moving surface method, Int. Arch. Photogramm. Remote Sens., 35, 213

Forlani, 2006, Complete classification of raw LIDAR and 3D reconstruction of buildings, Pattern Anal. Appl., 8, 357, 10.1007/s10044-005-0018-2

Brenner, 2005, Building reconstruction from images and laser scanning, Int. J. Appl. Earth Obs. Geoinf., 6, 187

Li, 2013, New methodologies for precise building boundary extraction from LiDAR data and high resolution image, Sensor Rev., 2, 157, 10.1108/02602281311299699

Li, 2013, An improved building boundary extraction algorithm based on fusion of optical imagery and LIDAR data, Optik, 124, 5357, 10.1016/j.ijleo.2013.03.045

Hildebrandt, K., Polthier, K., and Wardetzky, M. (2005, January 4–6). Smooth feature lines on surface meshes. Proceedings of the 3rd Eurographics Symposium on Geometry Processing, Vienna, Austria.

Altantsetseg, 2013, Feature line extraction from unorganized noisy point clouds using truncated Fourier series, Visual Comput., 29, 617, 10.1007/s00371-013-0800-x

Huang, 2001, Automatic data segmentation for geometric feature extraction from unorganized 3-D coordinate points, IEEE Trans. Robot. Autom., 17, 268, 10.1109/70.938384

Gumhold, S., Wang, X., and Macleod, R. (2001, January 7–10). Feature extraction from point clouds. Proceedings of the 10th International Meshing Roundtable, Sandia National Laboratory, Newport Beach, CA, USA.

Linsen, L., and Prautzsch, H. (2001, January 2–3). Local versus global triangulations. Proceedings of the EUROGRAPHICS 2001, Manchester, UK.

Laefer, 2013, Combining an angle criterion with voxelization and the flying voxel method in reconstructing building models from LiDAR data, Comput. Aided Civ. Inf., 28, 112, 10.1111/j.1467-8667.2012.00761.x

Linsen, L., and Prautzsch, H. (2002, January 7–12). Fan clouds—An alternative to meshes. Proceedings of the 11th International Workshop on Theoretical Foundations of Computer Vision, Dagstuhl Castle, Germany.

PCL-The Point Cloud Library. Available online: http://pointclouds.org/.

Bendels, 2006, Detecting holes in point set surfaces, J. WSCG, 14, 89

Zhang, 2013, SVM-based classification of segmented airborne LiDAR point clouds in urban area, Remote Sens., 5, 3749, 10.3390/rs5083749

Vosselman, 2004, Recognize structure in laser scanning point clouds, Int. Arch. Photogramm. Remote Sens., 46, 33

CloudCompare-3D Point Cloud and Mesh Processing Software. Available online: http://www.danielgm.net/cc/.

DTK-The 3D ToolKit. Available online: http://slam6d.sourceforge.net.

Wikipedia, the Free Encyclopedia. Available online: https://en.wikipedia.org/wiki/Intersection_curve.