24.3.2 Buildings from Depth Data, LiDAR Data

Chapter Contents (Back)
Laser Scanners. LiDAR. Building Recognition.
See also Building Footprints.
See also Buildings from Terrestrial Laser Data, Mobile Scanners, Ground-Based LiDAR.
See also Buildings DSM, DEM, Elevation, Surface Models.

ISPRS Test Project on Urban Classification and 3D Building Reconstruction,
LIDAR data for building descrtiptions.
WWW Link. Dataset, Building Extraction. Used for ISPRS 3D Labeling contest.

Hug, C.,
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Ascona97(203-212). BibRef 9700

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PandRS(53), No. 5, October 1998, pp. 286-295. From 3-D point clouds. BibRef 9810

Gruen, A.[Armin], Wang, X.H.[Xin-Hua],
News from CyberCity-Modeler,
Ascona01(93-101). Semi-automated system for buildings and other urban features. Editing functionality, topology, facades. 0201
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Sinning-Meister, M., Gruen, A., Dan, H.,
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PandRS(51), No. 4, August 1996, pp. 196-208.
Elsevier DOI Building Recognition. Award, U.V. Helava, ISPRS. BibRef 9608

Gruen, A., Dan, H.,
TOBAGO: A Topology Builder for the Automated Generation of Building Models,
Ascona97(149-160). BibRef 9700

Gruen, A.,
TOBAGO: A Semiautomated Approach for the Generation of 3-D Building Models,
PandRS(53), No. 2, April 1998, pp. 108-118. 9805
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Murai, S.J.[Shun-Ji], Phonekeo, V.[Vivarad], Ono, K.[Kunihiko], Yasue, S.[Shigetaka],
Development of polygon shift method for generating 3D view map of buildings,
PandRS(54), No. 5-6, December 1999, pp. 342-351. 0002
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Beraldin, J.A.[J. Angelo], Blais, F., Boulanger, P., Cournoyer, L., Domey, J., El-Hakim, S.F., Godin, G., Rioux, M., Taylor, J.,
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PandRS(55), No. 4, November 2000, pp. 230-250. Laser Scanner results, both small scale and building scale. 0101
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Nardinocchi, C.[Carla], Forlani, G.[Gianfranco],
Building Detection and Roof Extraction in Laser Scanning Data,
Ascona01(319-328). Remove terrain by smooth interpolation, grow regions to extract elevated areas. Classify regions as slopes, ridges, outlines. Fit planar surfaces. 0201
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Zingaretti, P.[Primo], Frontoni, E.[Emanuele], Forlani, G.[Gianfranco], Nardinocchi, C.[Carla],
Automatic extraction of LIDAR data classification rules,
CIAP07(273-278).
IEEE DOI 0709
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Forlani, G.[Gianfranco], Nardinocchi, C.[Carla],
Adaptive Filtering of Aerial Laser Scanning Data,
Laser07(130).
PDF File. 0709
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Fujii, K., Arikawa, T.,
Urban object reconstruction using airborne laser elevation image and aerial image,
GeoRS(40), No. 10, October 2002, pp. 2234-2240.
IEEE Top Reference. 0301
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Rau, J.Y.[Jiann-Yeou], Chen, L.C.[Liang-Chien],
Robust Reconstruction of Building Models from Three-Dimensional Line Segments,
PhEngRS(69), No. 2, February 2003, pp. 181-188. The experimental results indicate that the proposed method can soundly rebuild the topology from 3D line segments and reconstruct building models with up to a 98 percent success rate.
WWW Link. 0304
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Chen, L.C.[Liang-Chien], Teo, T.A.[Tee-Ann], Hsieh, C.H.[Chi-Heng], Rau, J.Y.[Jiann-Yeou],
Reconstruction of Building Models with Curvilinear Boundaries from Laser Scanner and Aerial Imagery,
PSIVT06(24-33).
Springer DOI 0612
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Hu, J.H.[Jin-Hui], You, S.[Suya], and Neumann, U.[Ulrich],
Approaches to Large-Scale Urban Modeling,
IEEE_CGA(23), No. 6, November/December, 2003, pp. 62-69.
HTML Version. BibRef 0311

Rottensteiner, F.[Franz],
Automatic Generation of High-Quality Building Models from Lidar Data,
IEEE_CGA(23), No. 6, November/December, 2003, pp. 42-50.
HTML Version. BibRef 0311

Rottensteiner, F.[Franz], Briese, C.[Christian],
A New Method for Building Extraction in Urban Areas from High-Resolution LIDAR Data,
PCV02(A: 295). 0305
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Rottensteiner, F.[Franz],
Consistent Estimation of Building Parameters Considering Geometric Regularities by Soft Constraints,
PCV06(xx-yy).
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Niemeyer, J., Rottensteiner, F., Soergel, U., Heipke, C.,
Contextual Classification of Point Clouds Using a Two-Stage CRF,
PIA15(141-148).
DOI Link 1504
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Niemeyer, J., Rottensteiner, F., Soergel, U.,
Conditional Random Fields For Lidar Point Cloud Classification In Complex Urban Areas,
AnnalsPRS(I-3), No. 2012, pp. 263-268.
DOI Link 1209
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Niemeyer, J., Mallet, C., Rottensteiner, F., Sörgel, U.,
Conditional Random Fields for the Classification of LiDAR Point Clouds,
HighRes11(xx-yy).
PDF File. 1106
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Niemeyer, J.[Joachim], Wegner, J.D.[Jan Dirk], Mallet, C.[Clément], Rottensteiner, F.[Franz], Soergel, U.[Uwe],
Conditional Random Fields for Urban Scene Classification with Full Waveform LiDAR Data,
PIA11(233-244).
Springer DOI 1110
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Niemeyer, J.[Joachim], Rottensteiner, F.[Franz], Soergel, U.[Uwe],
Contextual classification of lidar data and building object detection in urban areas,
PandRS(87), No. 1, 2014, pp. 152-165.
Elsevier DOI 1402
LIDAR BibRef

Chehata, N.[Nesrine], Guo, L.[Li], Mallet, C.[Clément],
Contribution of airborne full-waveform lidar and image data for urban scene classification,
ICIP09(1669-1672).
IEEE DOI 0911
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And:
Airborne Lidar feature Selection for urban classification using random forests,
Laser09(207). 0909
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Sohn, G.H.[Gun-Ho], Dowman, I.J.[Ian J.],
Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction,
PandRS(62), No. 1, May 2007, pp. 43-63.
Elsevier DOI 0709
BibRef
Earlier:
Extraction of Buildings from High-Resolution Satellite Data,
Ascona01(345-355). Find dominant edge direction to limit edges. 0201
Building extraction; LiDAR; IKONOS; Fusion; Binary space partitioning BibRef

Lu, Y.H.[Yi Hui], Trinder, J.C.[John C.], Kubik, K.[Kurt],
Automatic Building Detection Using the Dempster-Shafer Algorithm,
PhEngRS(72), No. 4, April 2006, pp. 395-404.
WWW Link. 0610
A strategy for the automatic detection of buildings from aerial images using combined image analysis and data fusion. BibRef

Rottensteiner, F., Trinder, J.C., Clode, S.P., Kubik, K., Lovell, B.,
Building detection by Dempster-Shafer fusion of lidar data and multispectral aerial imagery,
ICPR04(II: 339-342).
IEEE DOI 0409
BibRef

Rottensteiner, F.[Franz], Trinder, J.[John], Clode, S.P.[Simon P.], Kubik, K.[Kurt],
Building detection by fusion of airborne laser scanner data and multi-spectral images: Performance evaluation and sensitivity analysis,
PandRS(62), No. 2, June 2007, pp. 135-149.
Elsevier DOI 0709
Building detection; Airborne laser scanning; Data fusion; Classification; Evaluation
See also Detection and Vectorization of Roads from Lidar Data. BibRef

Ma, R.J.[Rui-Jin], Meyer, W.[Will],
DTM Generation and Building Detection from Lidar Data,
PhEngRS(71), No. 7, July 2005, pp. 847-854. Describing a method to perform DTM generation and building detection from lidar range data through a segmentation process, and a method to conduct boundary regularization.
WWW Link. 0509
BibRef

Lee, D.H.[Dong Hyuk], Lee, K.M.[Kyoung Mu], Lee, S.U.[Sang Uk],
Fusion of Lidar and Imagery for Reliable Building Extraction,
PhEngRS(74), No. 2, February 2008, pp. 215-226.
WWW Link. 0803
The fusion of lidar and photogrammetric imagery for precise and automatic building extraction using line segments matching and perceptual grouping. BibRef

Chen, J.[Jie], Chen, B.Q.[Bao-Quan],
Architectural Modeling from Sparsely Scanned Range Data,
IJCV(78), No. 2-3, July 2008, pp. 223-236.
Springer DOI 0803
BibRef

Sohn, G.[Gunho], Huang, X.F.[Xian-Feng], Tao, V.[Vincent],
Using a Binary Space Partitioning Tree for Reconstructing Polyhedral Building Models from Airborne Lidar Data,
PhEngRS(74), No. 11, November 2008, pp. 1425-1440.
WWW Link. 0804
A complex building model, which includes a mixture of fl at and sloped planes, is simultaneously reconstructed using a coarse to fine approach accomplished by recursively partitioning an initial building region with data-driven linear features into a set of convex planar polygons having maximal co-planarity. BibRef

Chen, L.C.[Liang-Chien], Teo, T.A.[Tee-Ann], Kuo, C.Y.[Chih-Yi], Rau, J.Y.[Jiann-Yeou],
Shaping Polyhedral Buildings by the Fusion of Vector Maps and Lidar Point Clouds,
PhEngRS(74), No. 9, September 2008, pp. 1147-1158.
WWW Link. 0804
A scheme for the shaping of polyhedral buildings by the fusion of vector maps and lidar point clouds. BibRef

Rau, J.Y.[Jiann-Yeou], Teo, T.A.[Tee-Ann], Chen, L.C.[Liang-Chien], Tsai, F.[Fuan], Hsiao, K.H.[Kuo-Hsin], Hsu, W.C.[Wei-Chen],
Integration of GPS, GIS and Photogrammetry for Texture Mapping in Photo-Realistic City Modeling,
PSIVT06(1283-1292).
Springer DOI 0612
BibRef

Matikainen, L.[Leena], Hyyppä, J.[Juha], Kaartinen, H.[Harri],
Comparison Between First Pulse and Last Pulse Laser Scanner Data in the Automatic Detection of Buildings,
PhEngRS(75), No. 2, February 2009, pp. 133-146.
WWW Link. 0902
BibRef
Earlier: A1, A3, A2:
Classification Tree Based Building Detection From Laser Scanner and Aerial Image Data,
Laser07(280).
PDF File. 0709
The use of last pulse instead of first pulse laser scanner data can improve the results of automatic building detection especially by decreasing the number of classification errors in the surroundings of the buildings and the number of false detections. BibRef

Akel, N.A.[Nizar Abo], Filin, S.[Sagi], Doytsher, Y.[Yerach],
Reconstruction of Complex Shape Buildings from Lidar Data Using Free Form Surfaces,
PhEngRS(75), No. 3, March 2009, pp. 271-280.
WWW Link. 0903
A lidar-based building-extraction model that supports the reconstruction of buildings with general, free-form shapes.
See also Orthogonal Polynomials Supported by Regional Growing Segmentation for the Extraction of Terrain from Lidar Data.
See also Polygonal Approach for Automation in Extraction of Serial Modular Roofs, A. BibRef

Cheuk, M.L.[Mang Lung], Yuan, M.[May],
Assessing Spatial Uncertainty of Lidar-derived Building Model: A Case Study in Downtown Oklahoma City,
PhEngRS(75), No. 3, March 2009, pp. 257-270.
WWW Link. 0903
Research assessing the spatial uncertainty of lidar-derived building model using downtown Oklahoma City as an example. BibRef

Meng, X.L.[Xue-Lian], Wang, L.[Le], Currit, N.[Nate],
Morphology-Based Building Detection from Airborne Lidar Data,
PhEngRS(75), No. 4, April 2009, pp. 437-444.
WWW Link. 0903
A morphological building detecting method to extract buildings by gradually removing non-building pixels based on ground filtering, size, shape, height, element structure, and the elevation difference between the first and last returns from interpolated lidar data.
See also multi-directional ground filtering algorithm for airborne LIDAR, A. BibRef

Hesami, R.[Reyhaneh], Bab Hadiashar, A.[Alireza], Hossein Nezhad, R.[Reza],
Range segmentation of large building exteriors: A hierarchical robust approach,
CVIU(114), No. 4, April 2010, pp. 475-490.
Elsevier DOI 1003
BibRef
Earlier:
A Novel Hierarchical Technique for Range Segmentation of Large Building Exteriors,
ISVC07(II: 75-85).
Springer DOI 0711
Large-scale range data; Range segmentation; Robust estimation; Historical building exteriors BibRef

Khoshelham, K.[Kourosh], Nardinocchi, C.[Carla], Frontoni, E.[Emanuele], Mancini, A.[Adriano], Zingaretti, P.[Primo],
Performance evaluation of automated approaches to building detection in multi-source aerial data,
PandRS(65), No. 1, January 2010, pp. 123-133.
Elsevier DOI 1001
Building detection; Automation; Classification; LiDAR; Map updating BibRef

Oude Elberink, S.[Sander], Vosselman, G.[George],
Quality analysis on 3D building models reconstructed from airborne laser scanning data,
PandRS(66), No. 2, March 2011, pp. 157-165.
Elsevier DOI 1103
Accuracy; Analysis; Three-dimensional; Building; Lidar BibRef

Xu, S., Oude Elberink, S.[Sander], Vosselman, G.[George],
Entities and Features for Classifcation of Airborne Laser Scanning Data In Urban Area,
AnnalsPRS(I-4), No. 2012, pp. 257-262.
DOI Link 1209
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You, R.J., Lin, B.C.,
A Quality Prediction Method for Building Model Reconstruction Using LiDAR Data and Topographic Maps,
GeoRS(49), No. 9, September 2011, pp. 3471-3480.
IEEE DOI 1109
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And: A2, A1:
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ISPRS12(XXXIX-B7:437-441).
DOI Link 1209
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Liu, L.Y.[Ling-Yun], Stamos, I.[Ioannis],
A systematic approach for 2D-image to 3D-range registration in urban environments,
CVIU(116), No. 1, January 2012, pp. 25-37.
Elsevier DOI 1112
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Earlier: VRML07(1-8).
IEEE DOI 0710
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Earlier:
Automatic 3D to 2D Registration for the Photorealistic Rendering of Urban Scenes,
CVPR05(II: 137-143).
IEEE DOI
PDF File. Matching, Surfaces. 0507
2D-to-3D Registration; Photorealistic 3D modeling BibRef

Stamos, I.[Ioannis], Allen, P.K.[Peter K.],
Automatic Registration of 2-D with 3-D Imagery in Urban Environments,
ICCV01(II: 731-736).
IEEE DOI
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3-D range data and 2-D image data. Vanishing points. BibRef

Stamos, I., Leordeanu, M.,
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CVPR03(II: 555-561).
IEEE DOI
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3DPVT04(447-454).
IEEE DOI 0412

See also New Methods for Digital Modeling of Historic Sites. BibRef

Hadjiliadis, O.[Olympia], Stamos, I.[Ioannis],
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3DPVT10(xx-yy).
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As the data arrives in 3D line scanner. BibRef

Stamos, I.[Ioannis],
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Chen, C.C.[Cecilia Chao], Stamos, I.[Ioannis],
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3DIM07(185-192).
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Friedman, S.[Sam], Stamos, I.[Ioannis],
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IJCV(102), No. 1-3, March 2013, pp. 112-128.
WWW Link. 1303
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3DIMPVT11(220-227).
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Friedman, S.[Sam], Stamos, I.[Ioannis],
Automatic Procedural Modeling of Tree Structures in Point Clouds Using Wavelets,
3DV13(215-222)
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Murphy, M.[Maurice], McGovern, E.[Eugene], Pavia, S.[Sara],
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Pakzad, K., Klink, A., Müterthies, A., Gröger, G.[Gerhard], Stroh, V.[Viktor], Plümer, L.[Lutz],
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Gonzalez-Aguilera, D., Crespo-Matellan, E., Hernandez-Lopez, D., Rodriguez-Gonzalvez, P.,
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Point cloud, Coarse registration, Voxelization, Planar surface, 4PCS, Urban scene BibRef

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Semantics, Deep learning, Image segmentation, Task analysis, Cognition, Feature extraction, urban scene point clouds BibRef

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Elsevier DOI 2109
Photogrammetry, Pointcloud, 3D Data, Semantic segmentation, Deep learning, Model generalization BibRef

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Ai, M.C.[Meng-Chi], Li, Z.X.[Zhi-Xin], Shan, J.[Jie],
Topologically Consistent Reconstruction for Complex Indoor Structures from Point Clouds,
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Su, Z.H.[Zhong-Hua], Gao, Z.J.[Zhen-Ji], Zhou, G.Y.[Gui-Yun], Li, S.H.[Shi-Hua], Song, L.H.[Li-Hui], Lu, X.[Xukun], Kang, N.[Ning],
Building Plane Segmentation Based on Point Clouds,
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Bouziani, M., Chaaba, H., Ettarid, M.,
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Automatic Filtering of Lidar Building Point Cloud in Case of Trees Associated to Building Roof,
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Gharineiat, Z.[Zahra], Kurdi, F.T.[Fayez Tarsha], Campbell, G.[Glenn],
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Point Cloud Validation: On the Impact of Laser Scanning Technologies on the Semantic Segmentation for BIM Modeling and Evaluation,
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Li, Z.X.[Zhi-Xin], Shan, J.[Jie],
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Elsevier DOI 2202
Building reconstruction, RANSAC, Point clouds, Building primitives, Optimal fitting BibRef

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Geometric Object Based Building Reconstruction From Satellite Imagery Derived Point Clouds,
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Li, Z.X.[Zhi-Xin], Zhang, W., Shan, J.[Jie],
Holistic Parametric Reconstruction of Building Models From Point Clouds,
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Huang, H.B.[Hua-Bing], Chen, P.[Peimin], Xu, X.Q.[Xiao-Qing], Liu, C.X.[Cai-Xia], Wang, J.[Jie], Liu, C.[Chong], Clinton, N.[Nicholas], Gong, P.[Peng],
Estimating building height in China from ALOS AW3D30,
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Elsevier DOI 2202
Building height, AW3D30, Urbanization, GEE BibRef

Min, X.Q.[Xiang-Qiang], Wang, Y.F.[Yan-Feng], Zhang, K.[Ka], Sheng, Y.[Yehua], Qin, J.R.[Jia-Rui], Huang, Y.[Yi],
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First Lidar Campaign in the Industrial Sites of Volta Redonda-RJ and Lorena-SP, Brazil,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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Liu, S.L.[Shao-Lei], Fu, K.[Kexue], Wang, M.[Manning], Song, Z.J.[Zhi-Jian],
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Huang, J.[Jin], Stoter, J.[Jantien], Peters, R.[Ravi], Nan, L.L.[Liang-Liang],
City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Clouds,
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Tian, P.J.[Peng-Ju], Hua, X.H.[Xiang-Hong], Tao, W.Y.[Wu-Yong], Zhang, M.[Miao],
Robust Extraction of 3D Line Segment Features from Unorganized Building Point Clouds,
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Lewandowicz, E.[Elzbieta], Kurdi, F.T.[Fayez Tarsha], Gharineiat, Z.[Zahra],
3D LoD2 and LoD3 Modeling of Buildings with Ornamental Towers and Turrets Based on LiDAR Data,
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Kurdi, F.T.[Fayez Tarsha], Lewandowicz, E.[Elzbieta], Gharineiat, Z.[Zahra], Shan, J.[Jie],
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Kaplan, G.[Gordana], Comert, R.[Resul], Kaplan, O.[Onur], Matci, D.K.[Dilek Kucuk], Avdan, U.[Ugur],
Using Machine Learning to Extract Building Inventory Information Based on LiDAR Data,
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Chen, Z.Y.[Zhai-Yu], Ledoux, H.[Hugo], Khademi, S.[Seyran], Nan, L.L.[Liang-Liang],
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PandRS(194), 2022, pp. 58-73.
Elsevier DOI 2212
3D reconstruction, Compact building model, Point cloud, Deep neural network, Implicit field BibRef

Tan, Y.[Yi], Chen, L.[Limei], Wang, Q.[Qian], Li, S.H.[Sheng-Han], Deng, T.[Ting], Tang, D.D.[Dong-Dong],
Geometric Quality Assessment of Prefabricated Steel Box Girder Components Using 3D Laser Scanning and Building Information Model,
RS(15), No. 3, 2023, pp. xx-yy.
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Marmol, U.[Urszula], Borowiec, N.[Natalia],
Analysis and Verification of Building Changes Based on Point Clouds from Different Sources and Time Periods,
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Yamashita, T.J.[Thomas J.], Wester, D.B.[David B.], Tewes, M.E.[Michael E.], Young, J.H.[John H.], Lombardi, J.V.[Jason V.],
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Camera and LiDAR Fusion for Urban Scene Reconstruction and Novel View Synthesis via Voxel-Based Neural Radiance Fields,
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Xiao, X.[Xiao], Liu, Y.H.[Yu-Hang], Zhang, Y.[Yanci],
Iterative Low-Poly Building Model Reconstruction from Mesh Soups Based on Contour,
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Li, Y.[Ying], Gong, G.H.[Guang-Hong], Liu, C.[Chen], Zhao, Y.[Yaopu], Qi, Y.J.[Yong-Jie], Lu, C.C.[Chuan-Chuan], Li, N.[Ni],
Hybrid Method of Connection Evaluation and Framework Optimization for Building Surface Reconstruction,
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Shi, M.[Minan], Zhang, F.[Fubo], Chen, L.Y.[Long-Yong], Liu, S.[Shuo], Yang, L.[Ling], Zhang, C.W.[Cheng-Wei],
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Pepe, M.[Massimiliano], Garofalo, A.R.[Alfredo Restuccia], Costantino, D.[Domenica], Tana, F.F.[Federica Francesca], Palumbo, D.[Donato], Alfio, V.S.[Vincenzo Saverio], Spacone, E.[Enrico],
From Point Cloud to BIM: A New Method Based on Efficient Point Cloud Simplification by Geometric Feature Analysis and Building Parametric Objects in Rhinoceros/Grasshopper Software,
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Schuegraf, P.[Philipp], Shan, J.[Jie], Bittner, K.[Ksenia],
PLANES4LOD2: Reconstruction of LoD-2 building models using a depth attention-based fully convolutional neural network,
PandRS(211), 2024, pp. 425-437.
Elsevier DOI Code:
WWW Link. 2405
Building reconstruction, Images, Digital surface model, Instance segmentation, Depth attention module BibRef

Su, Z.H.[Zhong-Hua], Peng, J.[Jing], Feng, D.[Dajian], Li, S.H.[Shi-Hua], Yuan, Y.[Yi], Zhou, G.Y.[Gui-Yun],
A Building Point Cloud Extraction Algorithm in Complex Scenes,
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Liu, Y.J.[Yu-Jia], Obukhov, A.[Anton], Wegner, J.D.[Jan Dirk], Schindler, K.[Konrad],
Point2Building: Reconstructing buildings from airborne LiDAR point clouds,
PandRS(215), 2024, pp. 351-368.
Elsevier DOI 2408
Airborne LiDAR point clouds, Deep learning, Building reconstruction, Autoregressive generative models, Transformers BibRef

Sulaiman, M.[Muhammad], Farmanbar, M.[Mina], Belbachir, A.N.[Ahmed Nabil], Rong, C.M.[Chun-Ming],
Genetic Algorithm Empowering Unsupervised Learning for Optimizing Building Segmentation from Light Detection and Ranging Point Clouds,
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Chen, Z.[Zhaiyu], Shi, Y.L.[Yi-Lei], Nan, L.L.[Liang-Liang], Xiong, Z.[Zhitong], Zhu, X.X.[Xiao Xiang],
PolyGNN: Polyhedron-based graph neural network for 3D building reconstruction from point clouds,
PandRS(218), 2024, pp. 693-706.
Elsevier DOI Code:
WWW Link. 2412
3D reconstruction, Building model, Graph neural network, Point cloud, Polyhedron BibRef

Wei, Y.[Yao], Vosselman, G.[George], Yang, M.Y.[Michael Ying],
BuilDiff: 3D Building Shape Generation using Single-Image Conditional Point Cloud Diffusion Models,
AI3DCC23(2902-2911)
IEEE DOI 2401
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Hong, Y.N.[Yi-Ning], Mo, K.C.[Kai-Chun], Yi, L.[Li], Guibas, L.J.[Leonidas J.], Torralba, A.[Antonio], Tenenbaum, J.B.[Joshua B.], Gan, C.[Chuang],
Fixing Malfunctional Objects With Learned Physical Simulation and Functional Prediction,
CVPR22(1403-1413)
IEEE DOI 2210
Point cloud compression, Solid modeling, Codes, Buildings, Predictive models, Segmentation, grouping and shape analysis BibRef

Langlois, P.A.[Pierre-Alain], Xiao, Y.[Yang], Boulch, A.[Alexandre], Marlet, R.[Renaud],
VASAD: a Volume and Semantic dataset for Building Reconstruction from Point Clouds,
ICPR22(4008-4015)
IEEE DOI 2212
Geometry, Point cloud compression, Surface reconstruction, Solid modeling, Semantics BibRef

Kada, M., Kuramin, D.,
ALS Point Cloud Classification Using Pointnet++ and Kpconv with Prior Knowledge,
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3D Content Generation Using Hybrid Aerial Sensor Data,
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Label-efficient Deep Learning-based Semantic Segmentation of Building Point Clouds At Lod3 Level,
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Gabara, G., Sawicki, P.,
Quality Evaluation of 3d Building Models Based on Low-altitude Imagery And Airborne Laser Scanning Point Clouds,
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Zou, Q., Sester, M.,
Incremental Map Refinement of Building Information Using LiDAR Point Clouds,
ISPRS21(B2-2021: 277-282).
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Automatic Segmentation of Point Clouds in the Architecture Environment,
ISPRS21(B2-2021: 215-221).
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Soilán, M., Justo, A., Sánchez-Rodríguez, A., Lamas, D., Riveiro, B.,
3d Point Cloud Data Processing and Infrastructure Information Models: Methods and Findings from Safeway Project,
ISPRS21(B2-2021: 239-246).
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Xie, Y., Schindler, K., Tian, J., Zhu, X.X.,
Exploring Cross-city Semantic Segmentation of ALS Point Clouds,
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Nurunnabi, A., Teferle, F.N., Li, J., Lindenbergh, R.C., Parvaz, S.,
Investigation of Pointnet for Semantic Segmentation of Large-scale Outdoor Point Clouds,
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Bouziani, M., Amraoui, M., Kellouch, S.,
Comparison Assessment of Digital 3d Models Obtained By Drone-based Lidar and Drone Imagery,
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Kurdi, F.T.[Fayez Tarsha], Gharineiat, Z.[Zahra], Campbell, G.[Glenn], Dey, E.K.[Emon Kumar], Awrangjeb, M.[Mohammad],
Full Series Algorithm of Automatic Building Extraction and Modelling from LiDAR Data,
DICTA21(01-08)
IEEE DOI 2201
Analytical models, Adaptation models, Laser radar, Buildings, Vegetation mapping, Vegetation, Filtering algorithms, LiDAR, Segmentation BibRef

Özdemir, E.[Emre], Remondino, F.[Fabio], Golkar, A.[Alessandro],
An Efficient and General Framework for Aerial Point Cloud Classification in Urban Scenarios,
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Building Features Recognition From Uncertain 3d Lidar Point Clouds: A Semantic Approach,
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Drešcek, U., Fras, M.K.[M. Kosmatin], Lisec, A., Grigillo, D.,
The Impact of Point Cloud Density on Building Outline Extraction,
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WuDunn, M., Dunn, J., Zakhor, A.,
Point Cloud Segmentation using RGB Drone Imagery,
ICIP20(2750-2754)
IEEE DOI 2011
Image segmentation, Cameras, Pipelines, Buildings, Semantics, Point Cloud BibRef

Varney, N., Asari, V.K., Graehling, Q.,
DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation,
EarthVision20(717-726)
IEEE DOI 2008
Laser radar, Semantics, Lasers, Machine learning, Buildings, Vegetation mapping BibRef

Román, J., Lerones, P.M., Llamas, J., Zalama, E., Gómez-García-Bermejo, J.,
Towards The Automatic 3d Parametrization of Non-planar Surfaces From Point Clouds in HBIM Applications,
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Murtiyoso, A., Grussenmeyer, P.,
Automatic Heritage Building Point Cloud Segmentation and Classification Using Geometrical Rules,
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Ghasemi Nejad, R., Pahlavani, P., Bigdeli, B.,
Automatic Building Extraction Using a Decision Tree Object-based Classification On Joint Use of Aerial and Lidar Data,
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Hujebri, B., Ebrahimikia, M., Enayati, H.,
Automatic Building Extraction From Lidar Point Cloud Data in The Fusion Of Orthoimage,
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dos Santos, R.C., Pessoa, G.G., Carrilho, A.C., Galo, M.,
Building Detection From Lidar Data Using Entropy and The K-means Concept,
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Jamali, A., Kumar, P., Abdul Rahman, A.,
Automated Extraction of Buildings From Aerial Lidar Point Clouds And Digital Imaging Datasets,
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Argiolas, R., Cazzani, A., Reccia, E., Bagnolo, V.,
From Lidar Data Towards HBIM for Structural Evaluation,
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Jones, M., Hippolite, N., Patel, R., Peters, S., Singh, P., Chen, C., Wunsche, B.C.,
Towards a Graph-Based Approach for Mesh Healing for Blocky Objects with Self-Similarities,
IVCNZ18(1-6)
IEEE DOI 1902
Buildings, Surface reconstruction, Solid modeling, Image reconstruction, Computational modeling, mesh filling BibRef

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Automated Building Detection In Dense Point Cloud and Update of Open Source Data Bases,
GeoInfo18(11-18).
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Paris-Lille-3D: A Point Cloud Dataset for Urban Scene Segmentation and Classification,
DeepLearnRV18(2108-21083)
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Urban areas, Laser radar, Benchmark testing, Robots, Autonomous vehicles BibRef

Cembranos, J.R.[Javier Román], Fernández, J.L.[José Llamas], Lerones, P.M.[Pedro Martín], García Bermejo, J.G.[Jaime Gómez], Casanova, E.Z.[Eduardo Zalama], Ioannides, M.[Marinos],
Supporting the Automatic Extraction of HBIM Elements from Point Clouds,
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Kudela, L.[László], Almac, U.[Umut], Kollmannsberger, S.[Stefan], Rank, E.[Ernst],
Direct Numerical Analysis of Historical Structures Represented by Point Clouds,
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Parida, G., Rajan, K.S.,
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3d Modeling of A Bazaar in Ancient Harran City Using Laser Scanning Technique,
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Nguatem, W., Mayer, H.,
Modeling Urban Scenes from Pointclouds,
ICCV17(3857-3866)
IEEE DOI 1802
Bayes methods, Boolean algebra, architectural CAD, buildings (structures), divide and conquer methods, BibRef

Nguatem, W., Drauschke, M., Meyer, H.,
Finding Cuboid-based Building Models In Point Clouds,
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CNN-Based Object Segmentation in Urban LIDAR with Missing Points,
3DV16(417-425)
IEEE DOI 1701
convolution BibRef

Guislain, M., Digne, J., Chaine, R., Kudelski, D., Lefebvre-Albaret, P.,
Detecting and Correcting Shadows in Urban Point Clouds and Image Collections,
3DV16(537-545)
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Buildings BibRef

Hamid-Lakzaeian, F.[Fatemeh], Laefer, D.F.[Debra F.],
An Integrated Octree-RANSAC Technique for Automated LiDAR Building Data Segmentation for Decorative Buildings,
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Affara, L.[Lama], Nan, L.L.[Liang-Liang], Ghanem, B.[Bernard], Wonka, P.[Peter],
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Nan, L.L.[Liang-Liang], Wonka, P.[Peter],
PolyFit: Polygonal Surface Reconstruction from Point Clouds,
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computational geometry, feature selection, image reconstruction, linear programming, mesh generation, BibRef

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Manhattan-World Urban Reconstruction from Point Clouds,
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Ding, L., Elliethy, A., Freedenberg, E., Wolf-Johnson, S.A., Romphf, J., Christensen, P., Sharma, G.,
Comparative analysis of homologous buildings using range imaging,
ICIP16(4378-4382)
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Heating BibRef

Xing, X.F.[Xu-Feng], Mostafavia, M.A.[Mir Abolfazl], Wang, C.[Chen],
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Yi, L.[Lina], Zhao, X.S.[Xue-Sheng], Li, L.[Luan], Zhang, G.F.[Gui-Feng],
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optical radar BibRef

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