Abstract

Laser point cloud registration is a key step in multisource laser scanning data fusion and application. Aimed at the problems of fewer overlapping regional features and the influence of building eaves on registration accuracy, a hierarchical registration algorithm of laser point clouds that considers building eave attributes is proposed in this paper. After extracting the building feature points of airborne and vehicle-borne light detection and ranging data, the similarity measurement model is constructed to carry out coarse registration based on pseudo-conjugate points. To obtain the feature points of the potential eaves (FPPE), the building contour lines of the vehicle-borne data are extended using the direction prediction algorithm. The FPPE data are regarded as the search set, in which the iterative closest point (ICP) algorithm is employed to match the true conjugate points between the airborne laser scanning data and vehicle-borne laser scanning data. The ICP algorithm is used again to complete the fine registration. To evaluate the registration performance, the developed method was applied to the data processing near Shandong University of Science and Technology, Qingdao, China. The experimental results showed that the FPPE dataset can effectively address the coarse registration accuracy effects on the convergence of the iterative ICP. Before considering eave attributes, the mean registration errors (MREs) of the proposed method in the $xoz$ plane, $yoz$ plane, and $xoy$ plane are 0.318, 0.96, and 0.786 m, respectively. After considering eave attributes, the MREs decrease to 0.129, 0.187, and 0.169 m, respectively. The developed method can effectively improve the registration accuracy of the laser point clouds, which not only solves the problem of matching true conjugate points under the effects of the eaves but also avoids converging to a local minimum due to ICP’s poor coarse registration.

© 2021 Optical Society of America

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  1. J. Shan and C. K. Toth, Topographic Laser Ranging and Scanning: Principles and Processing (CRC Press, 2008).
  2. K. I. Bang, A. F. Habib, K. Kusevic, and P. Mrstik, “Integration of terrestrial and airborne LiDAR data for system calibration,” Proceedings International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2008, pp. 391–398.
  3. M. J. Acuña, V. Matute, C. Chiriboga, and F. Castañeda, “The cultural and natural landscapes of El Tintal, Guatemala: preliminary results of the application of airborne LiDAR,” 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia, 2017.
  4. L. J. Quackenbush, I. Im, and Y. Zuo, “Road extraction: a review of LiDAR-focused studies,” in Remote Sensing of Natural Resources (2013), pp. 155–169.
  5. A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.
  6. I. Tomljenovic, B. Höfle, D. Tiede, and T. Blaschke, “Building extraction from airborne laser scanning data: an analysis of the state of the art,” Remote Sens. 7, 3826–3862 (2015).
    [Crossref]
  7. G. Gröger and L. Plümer, “CityGML–Interoperable semantic 3D city models,” ISPRS J. Photogramm. Remote Sens. 71, 12–33 (2012).
    [Crossref]
  8. M. Dwivedi, A. Uniyal, and R. Mohan, “New horizons in planning smart cities using LiDAR technology,” Int. J. Appl. Remote Sens. Gis (IJARSGIS) 2, 40–50 (2014).
  9. D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
    [Crossref]
  10. D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
    [Crossref]
  11. M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
    [Crossref]
  12. T.-A. Teo and S.-H. Huang, “Surface-based registration of airborne and terrestrial mobile LiDAR point clouds,” Remote Sens. 6, 12686 (2014).
    [Crossref]
  13. L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
    [Crossref]
  14. G. Heritage and A. Large, Laser Scanning for the Environmental Sciences (Wiley, 2009).
  15. B. Yang, Z. Dong, F. Liang, and Y. Liu, “Automatic registration of large-scale urban scene point clouds based on semantic feature points,” ISPRS J. Photogramm. Remote Sens. 113, 43–58 (2016).
    [Crossref]
  16. M. Mutlu, S. C. Popescu, C. Stripling, and T. Spencer, “Mapping surface fuel models using lidar and multispectral data fusion for fire behavior,” Remote Sens. Environ. 112, 274–285 (2008).
    [Crossref]
  17. L. Zhou and G. Vosselman, “Mapping curbstones in airborne and mobile laser scanning data,” Int. J. Appl. Earth Obs. Geoinf. 18, 293–304 (2012).
    [Crossref]
  18. J. Böhm and N. Haala, “Efficient integration of aerial and terrestrial laser data for virtual city modeling using lasermaps,” Proceedings of International Society of Photogrammetry and Remote Sensing (ISPRS) WG III/3, III/4, V/3 Workshop on Laser Scanning, Enschede, the Netherlands, 2005, pp. 12–14.
  19. J. Hohenthal, P. Alho, J. Hyyppa, and H. Hyyppa, “Laser scanning applications in fluvial studies,” Prog. Phys. Geogr. 35, 782–809 (2011).
    [Crossref]
  20. M. Hauglin, V. Lien, E. Næsset, and T. Gobakken, “Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data,” Int. J. Remote Sens. 35, 3135–3149 (2014).
    [Crossref]
  21. M. Bremer and O. Sass, “Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow event,” in Geomorphology-Amsterdam (2012).
  22. T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
    [Crossref]
  23. L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
    [Crossref]
  24. J. Salvi, C. Matabosch, D. Fofi, and J. Forest, “A review of recent range image registration methods with accuracy evaluation,” Image Vis. Comput. 25, 578–596 (2007).
    [Crossref]
  25. Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
    [Crossref]
  26. M. I. Restrepo, A. O. Ulusoy, and J. L. Mundy, “Evaluation of feature-based 3-d registration of probabilistic volumetric scenes,” ISPRS J. Photogramm. Remote Sens. 98, 1–18 (2014).
    [Crossref]
  27. P. J. Besl and N. D. McKay, “Method for registration of 3-D shapes,” Proc. SPIE 1611, 586–606 (1992).
    [Crossref]
  28. S. Rusinkiewicz and M. Levoy, “Efficient variants of the ICP algorithm,” in Proceedings 3rd International Conference on 3-D Digital Imaging and Modeling (IEEE, 2001), pp. 145–152.
  29. K.-H. Bae and D. D. Lichti, “A method for automated registration of unorganised point clouds,” ISPRS J. Photogramm. Remote Sens. 63, 36–54 (2008).
    [Crossref]
  30. L. Cheng, L. Tong, M. Li, and Y. Liu, “Semi-automatic registration of airborne and terrestrial laser scanning data using building corner matching with boundaries as reliability check,” Remote Sens. 5, 6260–6283 (2013).
    [Crossref]
  31. L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
    [Crossref]
  32. B. Yang, Y. Zang, Z. Dong, and R. Huang, “An automated method to register airborne and terrestrial laser scanning point clouds,” ISPRS J. Photogramm. Remote Sens. 109, 62–76 (2015).
    [Crossref]
  33. X. Cheng, X. Cheng, Q. Li, and L. Ma, “Automatic registration of terrestrial and airborne point clouds using building outline features,”IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing 11, 628–638 (2018).
    [Crossref]
  34. A. Gruen and D. Akca, “Least squares 3D surface and curve matching,” ISPRS J. Photogramm. Remote Sens. 59, 151–174 (2005).
    [Crossref]
  35. T.-Y. Chuang and J.-J. Jaw, “Multi-feature registration of point clouds,” Remote Sens. 9, 281–309 (2017).
    [Crossref]
  36. X. Wang, X. Ma, F. Yang, D. Su, and S. Xia, “An improved progressive TIN densification filtering algorithm for airborne LiDAR data based on a multiscale cylindrical neighborhood,” Appl. Opt. 59, 6540–6550 (2020).
    [Crossref]
  37. A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
    [Crossref]
  38. J. Sánchez-Lopera and J. L. Lerma, “Classification of lidar bare-earth points, buildings, vegetation, and small objects based on region growing and angular classifier,” Int. J. Remote Sens. 35, 6955–6972 (2014).
    [Crossref]
  39. J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
    [Crossref]
  40. B. Yang, Z. Wei, Q. Li, and J. Li, “Semiautomated building facade footprint extraction from mobile LiDAR point clouds,” IEEE Geosci. Remote Sens. Lett. 10, 766–770 (2012).
    [Crossref]
  41. F. Pauling, M. Bosse, and R. Zlot, “Automatic segmentation of 3d laser point clouds by ellipsoidal region growing,” Australasian Conference on Robotics and Automation, Sydney, Australia, 2009.
  42. Y. He, C. Zhang, and C. S. Fraser, “An energy minimization approach to automated extraction of regular building footprints from airborne LiDAR data,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. II-3, 65–72 (2014).
    [Crossref]
  43. M. A. Fischler and R. C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun. ACM 24, 381–395 (1981).
    [Crossref]
  44. H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
    [Crossref]
  45. V. Ramasubramanian and K. K. Paliwal, “Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding,” IEEE Trans. Signal Process. 40, 518–531 (1992).
    [Crossref]

2020 (3)

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

X. Wang, X. Ma, F. Yang, D. Su, and S. Xia, “An improved progressive TIN densification filtering algorithm for airborne LiDAR data based on a multiscale cylindrical neighborhood,” Appl. Opt. 59, 6540–6550 (2020).
[Crossref]

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

2019 (1)

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

2018 (3)

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

X. Cheng, X. Cheng, Q. Li, and L. Ma, “Automatic registration of terrestrial and airborne point clouds using building outline features,”IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing 11, 628–638 (2018).
[Crossref]

2017 (1)

T.-Y. Chuang and J.-J. Jaw, “Multi-feature registration of point clouds,” Remote Sens. 9, 281–309 (2017).
[Crossref]

2016 (1)

B. Yang, Z. Dong, F. Liang, and Y. Liu, “Automatic registration of large-scale urban scene point clouds based on semantic feature points,” ISPRS J. Photogramm. Remote Sens. 113, 43–58 (2016).
[Crossref]

2015 (4)

I. Tomljenovic, B. Höfle, D. Tiede, and T. Blaschke, “Building extraction from airborne laser scanning data: an analysis of the state of the art,” Remote Sens. 7, 3826–3862 (2015).
[Crossref]

L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
[Crossref]

L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
[Crossref]

B. Yang, Y. Zang, Z. Dong, and R. Huang, “An automated method to register airborne and terrestrial laser scanning point clouds,” ISPRS J. Photogramm. Remote Sens. 109, 62–76 (2015).
[Crossref]

2014 (7)

T.-A. Teo and S.-H. Huang, “Surface-based registration of airborne and terrestrial mobile LiDAR point clouds,” Remote Sens. 6, 12686 (2014).
[Crossref]

Y. He, C. Zhang, and C. S. Fraser, “An energy minimization approach to automated extraction of regular building footprints from airborne LiDAR data,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. II-3, 65–72 (2014).
[Crossref]

J. Sánchez-Lopera and J. L. Lerma, “Classification of lidar bare-earth points, buildings, vegetation, and small objects based on region growing and angular classifier,” Int. J. Remote Sens. 35, 6955–6972 (2014).
[Crossref]

Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
[Crossref]

M. I. Restrepo, A. O. Ulusoy, and J. L. Mundy, “Evaluation of feature-based 3-d registration of probabilistic volumetric scenes,” ISPRS J. Photogramm. Remote Sens. 98, 1–18 (2014).
[Crossref]

M. Hauglin, V. Lien, E. Næsset, and T. Gobakken, “Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data,” Int. J. Remote Sens. 35, 3135–3149 (2014).
[Crossref]

M. Dwivedi, A. Uniyal, and R. Mohan, “New horizons in planning smart cities using LiDAR technology,” Int. J. Appl. Remote Sens. Gis (IJARSGIS) 2, 40–50 (2014).

2013 (1)

L. Cheng, L. Tong, M. Li, and Y. Liu, “Semi-automatic registration of airborne and terrestrial laser scanning data using building corner matching with boundaries as reliability check,” Remote Sens. 5, 6260–6283 (2013).
[Crossref]

2012 (5)

G. Gröger and L. Plümer, “CityGML–Interoperable semantic 3D city models,” ISPRS J. Photogramm. Remote Sens. 71, 12–33 (2012).
[Crossref]

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

L. Zhou and G. Vosselman, “Mapping curbstones in airborne and mobile laser scanning data,” Int. J. Appl. Earth Obs. Geoinf. 18, 293–304 (2012).
[Crossref]

B. Yang, Z. Wei, Q. Li, and J. Li, “Semiautomated building facade footprint extraction from mobile LiDAR point clouds,” IEEE Geosci. Remote Sens. Lett. 10, 766–770 (2012).
[Crossref]

2011 (1)

J. Hohenthal, P. Alho, J. Hyyppa, and H. Hyyppa, “Laser scanning applications in fluvial studies,” Prog. Phys. Geogr. 35, 782–809 (2011).
[Crossref]

2008 (2)

M. Mutlu, S. C. Popescu, C. Stripling, and T. Spencer, “Mapping surface fuel models using lidar and multispectral data fusion for fire behavior,” Remote Sens. Environ. 112, 274–285 (2008).
[Crossref]

K.-H. Bae and D. D. Lichti, “A method for automated registration of unorganised point clouds,” ISPRS J. Photogramm. Remote Sens. 63, 36–54 (2008).
[Crossref]

2007 (1)

J. Salvi, C. Matabosch, D. Fofi, and J. Forest, “A review of recent range image registration methods with accuracy evaluation,” Image Vis. Comput. 25, 578–596 (2007).
[Crossref]

2005 (1)

A. Gruen and D. Akca, “Least squares 3D surface and curve matching,” ISPRS J. Photogramm. Remote Sens. 59, 151–174 (2005).
[Crossref]

2000 (1)

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

1992 (2)

V. Ramasubramanian and K. K. Paliwal, “Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding,” IEEE Trans. Signal Process. 40, 518–531 (1992).
[Crossref]

P. J. Besl and N. D. McKay, “Method for registration of 3-D shapes,” Proc. SPIE 1611, 586–606 (1992).
[Crossref]

1981 (1)

M. A. Fischler and R. C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun. ACM 24, 381–395 (1981).
[Crossref]

Acuña, M. J.

M. J. Acuña, V. Matute, C. Chiriboga, and F. Castañeda, “The cultural and natural landscapes of El Tintal, Guatemala: preliminary results of the application of airborne LiDAR,” 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia, 2017.

Akca, D.

A. Gruen and D. Akca, “Least squares 3D surface and curve matching,” ISPRS J. Photogramm. Remote Sens. 59, 151–174 (2005).
[Crossref]

Alho, P.

J. Hohenthal, P. Alho, J. Hyyppa, and H. Hyyppa, “Laser scanning applications in fluvial studies,” Prog. Phys. Geogr. 35, 782–809 (2011).
[Crossref]

Bae, K.-H.

K.-H. Bae and D. D. Lichti, “A method for automated registration of unorganised point clouds,” ISPRS J. Photogramm. Remote Sens. 63, 36–54 (2008).
[Crossref]

Bang, K. I.

K. I. Bang, A. F. Habib, K. Kusevic, and P. Mrstik, “Integration of terrestrial and airborne LiDAR data for system calibration,” Proceedings International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2008, pp. 391–398.

Bater, C. W.

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Becht, M.

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

Bennamoun, M.

Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
[Crossref]

Besl, P. J.

P. J. Besl and N. D. McKay, “Method for registration of 3-D shapes,” Proc. SPIE 1611, 586–606 (1992).
[Crossref]

Bianchi, M. G.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Bignami, C.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Bimböse, M.

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

Blaschke, T.

I. Tomljenovic, B. Höfle, D. Tiede, and T. Blaschke, “Building extraction from airborne laser scanning data: an analysis of the state of the art,” Remote Sens. 7, 3826–3862 (2015).
[Crossref]

Böhm, J.

J. Böhm and N. Haala, “Efficient integration of aerial and terrestrial laser data for virtual city modeling using lasermaps,” Proceedings of International Society of Photogrammetry and Remote Sensing (ISPRS) WG III/3, III/4, V/3 Workshop on Laser Scanning, Enschede, the Netherlands, 2005, pp. 12–14.

Bolles, R. C.

M. A. Fischler and R. C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun. ACM 24, 381–395 (1981).
[Crossref]

Bonali, E.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Bosse, M.

F. Pauling, M. Bosse, and R. Zlot, “Automatic segmentation of 3d laser point clouds by ellipsoidal region growing,” Australasian Conference on Robotics and Automation, Sydney, Australia, 2009.

Bremer, M.

M. Bremer and O. Sass, “Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow event,” in Geomorphology-Amsterdam (2012).

Castañeda, F.

M. J. Acuña, V. Matute, C. Chiriboga, and F. Castañeda, “The cultural and natural landscapes of El Tintal, Guatemala: preliminary results of the application of airborne LiDAR,” 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia, 2017.

Casula, G.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Chen, S.

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

Chen, Y.

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
[Crossref]

L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
[Crossref]

Cheng, L.

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
[Crossref]

L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
[Crossref]

L. Cheng, L. Tong, M. Li, and Y. Liu, “Semi-automatic registration of airborne and terrestrial laser scanning data using building corner matching with boundaries as reliability check,” Remote Sens. 5, 6260–6283 (2013).
[Crossref]

Cheng, X.

X. Cheng, X. Cheng, Q. Li, and L. Ma, “Automatic registration of terrestrial and airborne point clouds using building outline features,”IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing 11, 628–638 (2018).
[Crossref]

X. Cheng, X. Cheng, Q. Li, and L. Ma, “Automatic registration of terrestrial and airborne point clouds using building outline features,”IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing 11, 628–638 (2018).
[Crossref]

Chiriboga, C.

M. J. Acuña, V. Matute, C. Chiriboga, and F. Castañeda, “The cultural and natural landscapes of El Tintal, Guatemala: preliminary results of the application of airborne LiDAR,” 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia, 2017.

Chuang, T.-Y.

T.-Y. Chuang and J.-J. Jaw, “Multi-feature registration of point clouds,” Remote Sens. 9, 281–309 (2017).
[Crossref]

Coops, N. C.

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Crosetto, M.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Dong, Z.

B. Yang, Z. Dong, F. Liang, and Y. Liu, “Automatic registration of large-scale urban scene point clouds based on semantic feature points,” ISPRS J. Photogramm. Remote Sens. 113, 43–58 (2016).
[Crossref]

B. Yang, Y. Zang, Z. Dong, and R. Huang, “An automated method to register airborne and terrestrial laser scanning point clouds,” ISPRS J. Photogramm. Remote Sens. 109, 62–76 (2015).
[Crossref]

Dwivedi, M.

M. Dwivedi, A. Uniyal, and R. Mohan, “New horizons in planning smart cities using LiDAR technology,” Int. J. Appl. Remote Sens. Gis (IJARSGIS) 2, 40–50 (2014).

Fischler, M. A.

M. A. Fischler and R. C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun. ACM 24, 381–395 (1981).
[Crossref]

Fofi, D.

J. Salvi, C. Matabosch, D. Fofi, and J. Forest, “A review of recent range image registration methods with accuracy evaluation,” Image Vis. Comput. 25, 578–596 (2007).
[Crossref]

Forest, J.

J. Salvi, C. Matabosch, D. Fofi, and J. Forest, “A review of recent range image registration methods with accuracy evaluation,” Image Vis. Comput. 25, 578–596 (2007).
[Crossref]

Fraser, C. S.

Y. He, C. Zhang, and C. S. Fraser, “An energy minimization approach to automated extraction of regular building footprints from airborne LiDAR data,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. II-3, 65–72 (2014).
[Crossref]

Gobakken, T.

M. Hauglin, V. Lien, E. Næsset, and T. Gobakken, “Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data,” Int. J. Remote Sens. 35, 3135–3149 (2014).
[Crossref]

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Gröger, G.

G. Gröger and L. Plümer, “CityGML–Interoperable semantic 3D city models,” ISPRS J. Photogramm. Remote Sens. 71, 12–33 (2012).
[Crossref]

Gruen, A.

A. Gruen and D. Akca, “Least squares 3D surface and curve matching,” ISPRS J. Photogramm. Remote Sens. 59, 151–174 (2005).
[Crossref]

Guo, Y.

Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
[Crossref]

Haala, N.

J. Böhm and N. Haala, “Efficient integration of aerial and terrestrial laser data for virtual city modeling using lasermaps,” Proceedings of International Society of Photogrammetry and Remote Sensing (ISPRS) WG III/3, III/4, V/3 Workshop on Laser Scanning, Enschede, the Netherlands, 2005, pp. 12–14.

Haas, F.

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

Habib, A. F.

K. I. Bang, A. F. Habib, K. Kusevic, and P. Mrstik, “Integration of terrestrial and airborne LiDAR data for system calibration,” Proceedings International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2008, pp. 391–398.

Hauglin, M.

M. Hauglin, V. Lien, E. Næsset, and T. Gobakken, “Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data,” Int. J. Remote Sens. 35, 3135–3149 (2014).
[Crossref]

He, Y.

Y. He, C. Zhang, and C. S. Fraser, “An energy minimization approach to automated extraction of regular building footprints from airborne LiDAR data,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. II-3, 65–72 (2014).
[Crossref]

Heckmann, T.

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

Heritage, G.

G. Heritage and A. Large, Laser Scanning for the Environmental Sciences (Wiley, 2009).

Hilker, T.

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Höfle, B.

I. Tomljenovic, B. Höfle, D. Tiede, and T. Blaschke, “Building extraction from airborne laser scanning data: an analysis of the state of the art,” Remote Sens. 7, 3826–3862 (2015).
[Crossref]

Hohenthal, J.

J. Hohenthal, P. Alho, J. Hyyppa, and H. Hyyppa, “Laser scanning applications in fluvial studies,” Prog. Phys. Geogr. 35, 782–809 (2011).
[Crossref]

Huang, J.

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

Huang, R.

B. Yang, Y. Zang, Z. Dong, and R. Huang, “An automated method to register airborne and terrestrial laser scanning point clouds,” ISPRS J. Photogramm. Remote Sens. 109, 62–76 (2015).
[Crossref]

Huang, S.-H.

T.-A. Teo and S.-H. Huang, “Surface-based registration of airborne and terrestrial mobile LiDAR point clouds,” Remote Sens. 6, 12686 (2014).
[Crossref]

Hyyppa, H.

J. Hohenthal, P. Alho, J. Hyyppa, and H. Hyyppa, “Laser scanning applications in fluvial studies,” Prog. Phys. Geogr. 35, 782–809 (2011).
[Crossref]

Hyyppa, J.

J. Hohenthal, P. Alho, J. Hyyppa, and H. Hyyppa, “Laser scanning applications in fluvial studies,” Prog. Phys. Geogr. 35, 782–809 (2011).
[Crossref]

Im, I.

L. J. Quackenbush, I. Im, and Y. Zuo, “Road extraction: a review of LiDAR-focused studies,” in Remote Sensing of Natural Resources (2013), pp. 155–169.

Jaw, J.-J.

T.-Y. Chuang and J.-J. Jaw, “Multi-feature registration of point clouds,” Remote Sens. 9, 281–309 (2017).
[Crossref]

Krautblatter, M.

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

Kusevic, K.

K. I. Bang, A. F. Habib, K. Kusevic, and P. Mrstik, “Integration of terrestrial and airborne LiDAR data for system calibration,” Proceedings International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2008, pp. 391–398.

Large, A.

G. Heritage and A. Large, Laser Scanning for the Environmental Sciences (Wiley, 2009).

Lerma, J. L.

J. Sánchez-Lopera and J. L. Lerma, “Classification of lidar bare-earth points, buildings, vegetation, and small objects based on region growing and angular classifier,” Int. J. Remote Sens. 35, 6955–6972 (2014).
[Crossref]

Levoy, M.

S. Rusinkiewicz and M. Levoy, “Efficient variants of the ICP algorithm,” in Proceedings 3rd International Conference on 3-D Digital Imaging and Modeling (IEEE, 2001), pp. 145–152.

Li, H.

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

Li, J.

B. Yang, Z. Wei, Q. Li, and J. Li, “Semiautomated building facade footprint extraction from mobile LiDAR point clouds,” IEEE Geosci. Remote Sens. Lett. 10, 766–770 (2012).
[Crossref]

Li, M.

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
[Crossref]

L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
[Crossref]

L. Cheng, L. Tong, M. Li, and Y. Liu, “Semi-automatic registration of airborne and terrestrial laser scanning data using building corner matching with boundaries as reliability check,” Remote Sens. 5, 6260–6283 (2013).
[Crossref]

Li, Q.

X. Cheng, X. Cheng, Q. Li, and L. Ma, “Automatic registration of terrestrial and airborne point clouds using building outline features,”IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing 11, 628–638 (2018).
[Crossref]

B. Yang, Z. Wei, Q. Li, and J. Li, “Semiautomated building facade footprint extraction from mobile LiDAR point clouds,” IEEE Geosci. Remote Sens. Lett. 10, 766–770 (2012).
[Crossref]

Liang, F.

B. Yang, Z. Dong, F. Liang, and Y. Liu, “Automatic registration of large-scale urban scene point clouds based on semantic feature points,” ISPRS J. Photogramm. Remote Sens. 113, 43–58 (2016).
[Crossref]

Lichti, D. D.

K.-H. Bae and D. D. Lichti, “A method for automated registration of unorganised point clouds,” ISPRS J. Photogramm. Remote Sens. 63, 36–54 (2008).
[Crossref]

Lien, V.

M. Hauglin, V. Lien, E. Næsset, and T. Gobakken, “Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data,” Int. J. Remote Sens. 35, 3135–3149 (2014).
[Crossref]

Liu, X.

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

Liu, Y.

B. Yang, Z. Dong, F. Liang, and Y. Liu, “Automatic registration of large-scale urban scene point clouds based on semantic feature points,” ISPRS J. Photogramm. Remote Sens. 113, 43–58 (2016).
[Crossref]

L. Cheng, L. Tong, M. Li, and Y. Liu, “Semi-automatic registration of airborne and terrestrial laser scanning data using building corner matching with boundaries as reliability check,” Remote Sens. 5, 6260–6283 (2013).
[Crossref]

Lu, M.

Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
[Crossref]

Luzi, G.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Ma, L.

X. Cheng, X. Cheng, Q. Li, and L. Ma, “Automatic registration of terrestrial and airborne point clouds using building outline features,”IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing 11, 628–638 (2018).
[Crossref]

Ma, W.

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

Ma, X.

Ma, Y.

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

Malik, J.

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

Matabosch, C.

J. Salvi, C. Matabosch, D. Fofi, and J. Forest, “A review of recent range image registration methods with accuracy evaluation,” Image Vis. Comput. 25, 578–596 (2007).
[Crossref]

Matute, V.

M. J. Acuña, V. Matute, C. Chiriboga, and F. Castañeda, “The cultural and natural landscapes of El Tintal, Guatemala: preliminary results of the application of airborne LiDAR,” 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia, 2017.

McKay, N. D.

P. J. Besl and N. D. McKay, “Method for registration of 3-D shapes,” Proc. SPIE 1611, 586–606 (1992).
[Crossref]

Mohan, R.

M. Dwivedi, A. Uniyal, and R. Mohan, “New horizons in planning smart cities using LiDAR technology,” Int. J. Appl. Remote Sens. Gis (IJARSGIS) 2, 40–50 (2014).

Montuori, A.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Morche, D.

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

Mrstik, P.

K. I. Bang, A. F. Habib, K. Kusevic, and P. Mrstik, “Integration of terrestrial and airborne LiDAR data for system calibration,” Proceedings International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2008, pp. 391–398.

Mundy, J. L.

M. I. Restrepo, A. O. Ulusoy, and J. L. Mundy, “Evaluation of feature-based 3-d registration of probabilistic volumetric scenes,” ISPRS J. Photogramm. Remote Sens. 98, 1–18 (2014).
[Crossref]

Mutlu, M.

M. Mutlu, S. C. Popescu, C. Stripling, and T. Spencer, “Mapping surface fuel models using lidar and multispectral data fusion for fire behavior,” Remote Sens. Environ. 112, 274–285 (2008).
[Crossref]

Næsset, E.

M. Hauglin, V. Lien, E. Næsset, and T. Gobakken, “Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data,” Int. J. Remote Sens. 35, 3135–3149 (2014).
[Crossref]

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Nelson, R. F.

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Ørka, H. O.

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Paliwal, K. K.

V. Ramasubramanian and K. K. Paliwal, “Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding,” IEEE Trans. Signal Process. 40, 518–531 (1992).
[Crossref]

Pan, L.

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

Pauling, F.

F. Pauling, M. Bosse, and R. Zlot, “Automatic segmentation of 3d laser point clouds by ellipsoidal region growing,” Australasian Conference on Robotics and Automation, Sydney, Australia, 2009.

Plümer, L.

G. Gröger and L. Plümer, “CityGML–Interoperable semantic 3D city models,” ISPRS J. Photogramm. Remote Sens. 71, 12–33 (2012).
[Crossref]

Popescu, S. C.

M. Mutlu, S. C. Popescu, C. Stripling, and T. Spencer, “Mapping surface fuel models using lidar and multispectral data fusion for fire behavior,” Remote Sens. Environ. 112, 274–285 (2008).
[Crossref]

Qi, C.

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

Qin, J.

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

Quackenbush, L. J.

L. J. Quackenbush, I. Im, and Y. Zuo, “Road extraction: a review of LiDAR-focused studies,” in Remote Sensing of Natural Resources (2013), pp. 155–169.

Ramasubramanian, V.

V. Ramasubramanian and K. K. Paliwal, “Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding,” IEEE Trans. Signal Process. 40, 518–531 (1992).
[Crossref]

Restrepo, M. I.

M. I. Restrepo, A. O. Ulusoy, and J. L. Mundy, “Evaluation of feature-based 3-d registration of probabilistic volumetric scenes,” ISPRS J. Photogramm. Remote Sens. 98, 1–18 (2014).
[Crossref]

Rusinkiewicz, S.

S. Rusinkiewicz and M. Levoy, “Efficient variants of the ICP algorithm,” in Proceedings 3rd International Conference on 3-D Digital Imaging and Modeling (IEEE, 2001), pp. 145–152.

Salvi, J.

J. Salvi, C. Matabosch, D. Fofi, and J. Forest, “A review of recent range image registration methods with accuracy evaluation,” Image Vis. Comput. 25, 578–596 (2007).
[Crossref]

Sánchez-Lopera, J.

J. Sánchez-Lopera and J. L. Lerma, “Classification of lidar bare-earth points, buildings, vegetation, and small objects based on region growing and angular classifier,” Int. J. Remote Sens. 35, 6955–6972 (2014).
[Crossref]

Sass, O.

M. Bremer and O. Sass, “Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow event,” in Geomorphology-Amsterdam (2012).

Shan, J.

J. Shan and C. K. Toth, Topographic Laser Ranging and Scanning: Principles and Processing (CRC Press, 2008).

Shi, J.

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

Sohel, F.

Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
[Crossref]

Spencer, T.

M. Mutlu, S. C. Popescu, C. Stripling, and T. Spencer, “Mapping surface fuel models using lidar and multispectral data fusion for fire behavior,” Remote Sens. Environ. 112, 274–285 (2008).
[Crossref]

Stramondo, S.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

Stripling, C.

M. Mutlu, S. C. Popescu, C. Stripling, and T. Spencer, “Mapping surface fuel models using lidar and multispectral data fusion for fire behavior,” Remote Sens. Environ. 112, 274–285 (2008).
[Crossref]

Su, D.

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

X. Wang, X. Ma, F. Yang, D. Su, and S. Xia, “An improved progressive TIN densification filtering algorithm for airborne LiDAR data based on a multiscale cylindrical neighborhood,” Appl. Opt. 59, 6540–6550 (2020).
[Crossref]

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

Teo, T.-A.

T.-A. Teo and S.-H. Huang, “Surface-based registration of airborne and terrestrial mobile LiDAR point clouds,” Remote Sens. 6, 12686 (2014).
[Crossref]

Tiede, D.

I. Tomljenovic, B. Höfle, D. Tiede, and T. Blaschke, “Building extraction from airborne laser scanning data: an analysis of the state of the art,” Remote Sens. 7, 3826–3862 (2015).
[Crossref]

Tomljenovic, I.

I. Tomljenovic, B. Höfle, D. Tiede, and T. Blaschke, “Building extraction from airborne laser scanning data: an analysis of the state of the art,” Remote Sens. 7, 3826–3862 (2015).
[Crossref]

Tong, L.

L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
[Crossref]

L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
[Crossref]

L. Cheng, L. Tong, M. Li, and Y. Liu, “Semi-automatic registration of airborne and terrestrial laser scanning data using building corner matching with boundaries as reliability check,” Remote Sens. 5, 6260–6283 (2013).
[Crossref]

Toth, C. K.

J. Shan and C. K. Toth, Topographic Laser Ranging and Scanning: Principles and Processing (CRC Press, 2008).

Ulusoy, A. O.

M. I. Restrepo, A. O. Ulusoy, and J. L. Mundy, “Evaluation of feature-based 3-d registration of probabilistic volumetric scenes,” ISPRS J. Photogramm. Remote Sens. 98, 1–18 (2014).
[Crossref]

Uniyal, A.

M. Dwivedi, A. Uniyal, and R. Mohan, “New horizons in planning smart cities using LiDAR technology,” Int. J. Appl. Remote Sens. Gis (IJARSGIS) 2, 40–50 (2014).

Vosselman, G.

L. Zhou and G. Vosselman, “Mapping curbstones in airborne and mobile laser scanning data,” Int. J. Appl. Earth Obs. Geoinf. 18, 293–304 (2012).
[Crossref]

Wan, J.

Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
[Crossref]

Wang, M.

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

Wang, X.

Wang, X. H.

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

Wei, Z.

B. Yang, Z. Wei, Q. Li, and J. Li, “Semiautomated building facade footprint extraction from mobile LiDAR point clouds,” IEEE Geosci. Remote Sens. Lett. 10, 766–770 (2012).
[Crossref]

White, J. C.

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Wu, Y.

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
[Crossref]

L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
[Crossref]

Wu, Z.

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

Wulder, M. A.

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

Xia, S.

Xiang, X.

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

Xiong, N. N.

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

Xu, H.

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

Yang, A.

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

Yang, B.

B. Yang, Z. Dong, F. Liang, and Y. Liu, “Automatic registration of large-scale urban scene point clouds based on semantic feature points,” ISPRS J. Photogramm. Remote Sens. 113, 43–58 (2016).
[Crossref]

B. Yang, Y. Zang, Z. Dong, and R. Huang, “An automated method to register airborne and terrestrial laser scanning point clouds,” ISPRS J. Photogramm. Remote Sens. 109, 62–76 (2015).
[Crossref]

B. Yang, Z. Wei, Q. Li, and J. Li, “Semiautomated building facade footprint extraction from mobile LiDAR point clouds,” IEEE Geosci. Remote Sens. Lett. 10, 766–770 (2012).
[Crossref]

Yang, F.

X. Wang, X. Ma, F. Yang, D. Su, and S. Xia, “An improved progressive TIN densification filtering algorithm for airborne LiDAR data based on a multiscale cylindrical neighborhood,” Appl. Opt. 59, 6540–6550 (2020).
[Crossref]

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

Zang, Y.

B. Yang, Y. Zang, Z. Dong, and R. Huang, “An automated method to register airborne and terrestrial laser scanning point clouds,” ISPRS J. Photogramm. Remote Sens. 109, 62–76 (2015).
[Crossref]

Zhang, C.

Y. He, C. Zhang, and C. S. Fraser, “An energy minimization approach to automated extraction of regular building footprints from airborne LiDAR data,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. II-3, 65–72 (2014).
[Crossref]

Zhang, K.

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

Zhao, D.

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

Zhou, L.

L. Zhou and G. Vosselman, “Mapping curbstones in airborne and mobile laser scanning data,” Int. J. Appl. Earth Obs. Geoinf. 18, 293–304 (2012).
[Crossref]

Zlot, R.

F. Pauling, M. Bosse, and R. Zlot, “Automatic segmentation of 3d laser point clouds by ellipsoidal region growing,” Australasian Conference on Robotics and Automation, Sydney, Australia, 2009.

Zuo, Y.

L. J. Quackenbush, I. Im, and Y. Zuo, “Road extraction: a review of LiDAR-focused studies,” in Remote Sensing of Natural Resources (2013), pp. 155–169.

Appl. Opt. (1)

Commun. ACM (1)

M. A. Fischler and R. C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,” Commun. ACM 24, 381–395 (1981).
[Crossref]

Earth Surf. Processes Landf. (1)

T. Heckmann, M. Bimböse, M. Krautblatter, F. Haas, M. Becht, and D. Morche, “From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany,” Earth Surf. Processes Landf. 37, 119–133 (2012).
[Crossref]

IEEE Access (1)

H. Li, J. Qin, X. Xiang, L. Pan, W. Ma, and N. N. Xiong, “An efficient image matching algorithm based on adaptive threshold and RANSAC,” IEEE Access 6, 66963–66971 (2018).
[Crossref]

IEEE Geosci. Remote Sens. Lett. (1)

B. Yang, Z. Wei, Q. Li, and J. Li, “Semiautomated building facade footprint extraction from mobile LiDAR point clouds,” IEEE Geosci. Remote Sens. Lett. 10, 766–770 (2012).
[Crossref]

IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing (1)

X. Cheng, X. Cheng, Q. Li, and L. Ma, “Automatic registration of terrestrial and airborne point clouds using building outline features,”IEEE J. Sel. Top. Appl. Earth Observ. Remote Sensing 11, 628–638 (2018).
[Crossref]

IEEE Trans. Geosci. Remote Sens. (2)

D. Su, F. Yang, Y. Ma, K. Zhang, J. Huang, and M. Wang, “Classification of coral reefs in the South China Sea by combining airborne LiDAR bathymetry bottom waveforms and bathymetric features,” IEEE Trans. Geosci. Remote Sens. 57, 6141–6149 (2019).
[Crossref]

D. Su, F. Yang, Y. Ma, X. H. Wang, A. Yang, and C. Qi, “Propagated uncertainty models arising from device, environment, and target for a small laser spot airborne LiDAR bathymetry and its verification in the South China Sea,” IEEE Trans. Geosci. Remote Sens. 58, 3213–3231 (2020).
[Crossref]

IEEE Trans. Pattern Anal. Mach. Intell. (2)

Y. Guo, M. Bennamoun, F. Sohel, M. Lu, and J. Wan, “3D object recognition in cluttered scenes with local surface features: a survey,” IEEE Trans. Pattern Anal. Mach. Intell. 36, 2270–2287 (2014).
[Crossref]

J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell. 22, 888–905 (2000).
[Crossref]

IEEE Trans. Signal Process. (1)

V. Ramasubramanian and K. K. Paliwal, “Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding,” IEEE Trans. Signal Process. 40, 518–531 (1992).
[Crossref]

Image Vis. Comput. (1)

J. Salvi, C. Matabosch, D. Fofi, and J. Forest, “A review of recent range image registration methods with accuracy evaluation,” Image Vis. Comput. 25, 578–596 (2007).
[Crossref]

Int. J. Appl. Earth Obs. Geoinf. (1)

L. Zhou and G. Vosselman, “Mapping curbstones in airborne and mobile laser scanning data,” Int. J. Appl. Earth Obs. Geoinf. 18, 293–304 (2012).
[Crossref]

Int. J. Appl. Remote Sens. Gis (IJARSGIS) (1)

M. Dwivedi, A. Uniyal, and R. Mohan, “New horizons in planning smart cities using LiDAR technology,” Int. J. Appl. Remote Sens. Gis (IJARSGIS) 2, 40–50 (2014).

Int. J. Remote Sens. (2)

M. Hauglin, V. Lien, E. Næsset, and T. Gobakken, “Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data,” Int. J. Remote Sens. 35, 3135–3149 (2014).
[Crossref]

J. Sánchez-Lopera and J. L. Lerma, “Classification of lidar bare-earth points, buildings, vegetation, and small objects based on region growing and angular classifier,” Int. J. Remote Sens. 35, 6955–6972 (2014).
[Crossref]

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. (1)

Y. He, C. Zhang, and C. S. Fraser, “An energy minimization approach to automated extraction of regular building footprints from airborne LiDAR data,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. II-3, 65–72 (2014).
[Crossref]

ISPRS J. Photogramm. Remote Sens. (7)

M. I. Restrepo, A. O. Ulusoy, and J. L. Mundy, “Evaluation of feature-based 3-d registration of probabilistic volumetric scenes,” ISPRS J. Photogramm. Remote Sens. 98, 1–18 (2014).
[Crossref]

B. Yang, Y. Zang, Z. Dong, and R. Huang, “An automated method to register airborne and terrestrial laser scanning point clouds,” ISPRS J. Photogramm. Remote Sens. 109, 62–76 (2015).
[Crossref]

K.-H. Bae and D. D. Lichti, “A method for automated registration of unorganised point clouds,” ISPRS J. Photogramm. Remote Sens. 63, 36–54 (2008).
[Crossref]

A. Gruen and D. Akca, “Least squares 3D surface and curve matching,” ISPRS J. Photogramm. Remote Sens. 59, 151–174 (2005).
[Crossref]

A. Yang, Z. Wu, F. Yang, D. Su, Y. Ma, D. Zhao, and C. Qi, “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation,” ISPRS J. Photogramm. Remote Sens. 163, 49–61 (2020).
[Crossref]

B. Yang, Z. Dong, F. Liang, and Y. Liu, “Automatic registration of large-scale urban scene point clouds based on semantic feature points,” ISPRS J. Photogramm. Remote Sens. 113, 43–58 (2016).
[Crossref]

G. Gröger and L. Plümer, “CityGML–Interoperable semantic 3D city models,” ISPRS J. Photogramm. Remote Sens. 71, 12–33 (2012).
[Crossref]

Proc. SPIE (1)

P. J. Besl and N. D. McKay, “Method for registration of 3-D shapes,” Proc. SPIE 1611, 586–606 (1992).
[Crossref]

Prog. Phys. Geogr. (1)

J. Hohenthal, P. Alho, J. Hyyppa, and H. Hyyppa, “Laser scanning applications in fluvial studies,” Prog. Phys. Geogr. 35, 782–809 (2011).
[Crossref]

Remote Sens. (6)

T.-A. Teo and S.-H. Huang, “Surface-based registration of airborne and terrestrial mobile LiDAR point clouds,” Remote Sens. 6, 12686 (2014).
[Crossref]

I. Tomljenovic, B. Höfle, D. Tiede, and T. Blaschke, “Building extraction from airborne laser scanning data: an analysis of the state of the art,” Remote Sens. 7, 3826–3862 (2015).
[Crossref]

L. Cheng, Y. Wu, L. Tong, Y. Chen, and M. Li, “Hierarchical registration method for airborne and vehicle lidar point cloud,” Remote Sens. 7, 13921–13944 (2015).
[Crossref]

T.-Y. Chuang and J.-J. Jaw, “Multi-feature registration of point clouds,” Remote Sens. 9, 281–309 (2017).
[Crossref]

L. Cheng, L. Tong, M. Li, and Y. Liu, “Semi-automatic registration of airborne and terrestrial laser scanning data using building corner matching with boundaries as reliability check,” Remote Sens. 5, 6260–6283 (2013).
[Crossref]

L. Cheng, L. Tong, Y. Wu, Y. Chen, and M. Li, “Shiftable leading point method for high accuracy registration of airborne and terrestrial LiDAR data,” Remote Sens. 7, 1915–1936 (2015).
[Crossref]

Remote Sens. Environ. (2)

M. A. Wulder, J. C. White, R. F. Nelson, E. Næsset, H. O. Ørka, N. C. Coops, T. Hilker, C. W. Bater, and T. Gobakken, “Lidar sampling for large-area forest characterization: a review,” Remote Sens. Environ. 121, 196–209 (2012).
[Crossref]

M. Mutlu, S. C. Popescu, C. Stripling, and T. Spencer, “Mapping surface fuel models using lidar and multispectral data fusion for fire behavior,” Remote Sens. Environ. 112, 274–285 (2008).
[Crossref]

Sensors (1)

L. Cheng, S. Chen, X. Liu, H. Xu, Y. Wu, M. Li, and Y. Chen, “Registration of laser scanning point clouds: a review,” Sensors 18, 1641 (2018).
[Crossref]

Other (10)

G. Heritage and A. Large, Laser Scanning for the Environmental Sciences (Wiley, 2009).

J. Böhm and N. Haala, “Efficient integration of aerial and terrestrial laser data for virtual city modeling using lasermaps,” Proceedings of International Society of Photogrammetry and Remote Sensing (ISPRS) WG III/3, III/4, V/3 Workshop on Laser Scanning, Enschede, the Netherlands, 2005, pp. 12–14.

J. Shan and C. K. Toth, Topographic Laser Ranging and Scanning: Principles and Processing (CRC Press, 2008).

K. I. Bang, A. F. Habib, K. Kusevic, and P. Mrstik, “Integration of terrestrial and airborne LiDAR data for system calibration,” Proceedings International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2008, pp. 391–398.

M. J. Acuña, V. Matute, C. Chiriboga, and F. Castañeda, “The cultural and natural landscapes of El Tintal, Guatemala: preliminary results of the application of airborne LiDAR,” 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia, 2017.

L. J. Quackenbush, I. Im, and Y. Zuo, “Road extraction: a review of LiDAR-focused studies,” in Remote Sensing of Natural Resources (2013), pp. 155–169.

A. Montuori, G. Luzi, S. Stramondo, G. Casula, C. Bignami, E. Bonali, M. G. Bianchi, and M. Crosetto, “Combined use of ground-based systems for Cultural Heritage conservation monitoring,” in IEEE Geoscience and Remote Sensing Symposium (IEEE, 2014), pp. 4086–4089.

M. Bremer and O. Sass, “Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow event,” in Geomorphology-Amsterdam (2012).

S. Rusinkiewicz and M. Levoy, “Efficient variants of the ICP algorithm,” in Proceedings 3rd International Conference on 3-D Digital Imaging and Modeling (IEEE, 2001), pp. 145–152.

F. Pauling, M. Bosse, and R. Zlot, “Automatic segmentation of 3d laser point clouds by ellipsoidal region growing,” Australasian Conference on Robotics and Automation, Sydney, Australia, 2009.

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Figures (12)

Fig. 1.
Fig. 1. Flowchart of the proposed method.
Fig. 2.
Fig. 2. Schematic of ALS and VLS feature extraction.
Fig. 3.
Fig. 3. Façades and eaves of common buildings.
Fig. 4.
Fig. 4. Schematic of FPPE position.
Fig. 5.
Fig. 5. Schematic diagram of the direction prediction algorithm.
Fig. 6.
Fig. 6. Experimental data. (a) Location and satellite image of the survey area; (b) ALS point clouds; (c) VLS point clouds.
Fig. 7.
Fig. 7. Extraction of building contour points and feature points. (a) ALS; (b) VLS; (c) and (d) details of (a) and (b), respectively.
Fig. 8.
Fig. 8. Matching result of conjugate points. (a) PCP matching; (b) VLS feature point adjustment; (c) and (d) details of (a) and (b), respectively.
Fig. 9.
Fig. 9. Comparison of point cloud registration results: (a) before registration; (b) registration of ignored eaves; and (c) registration of the proposed method. The bottom-right figure shows the partial enlarged view.
Fig. 10.
Fig. 10. Profiles of data before and after registration.
Fig. 11.
Fig. 11. Error distribution of checkpoints.
Fig. 12.
Fig. 12. Number of matching points in different threshold conditions.

Tables (3)

Tables Icon

Table 1. Parameter Settings

Tables Icon

Table 2. Calculated Rotation and Translation Parameters

Tables Icon

Table 3. Registration Accuracy

Equations (9)

Equations on this page are rendered with MathJax. Learn more.

ρ ( x ) = i = 1 k ( g i x g ¯ x ) ( g i x g ¯ x ) i = 1 k ( g i x g ¯ x ) 2 i = 1 k ( g i x g ¯ x ) 2 ,
ρ ( y ) = i = 1 k ( g i y g ¯ y ) ( g i y g ¯ y ) i = 1 k ( g i y g ¯ y ) 2 i = 1 k ( g i y g ¯ y ) 2 ,
S s i m = { [ a p v p ] | ( | ρ ( x ) | > T ρ ) ( | ρ ( y ) | > T ρ ) | a p O a p v p O v p | < T a | ( | a p O a p | | v p O v p | ) | < T d 1 } ,
[ X a l s Y a l s Z a l s ] = λ R ( α , β , γ ) [ X v l s Y v l s Z v l s ] + [ T x T y T z ] , R ( α , β , γ ) = R ( α ) R ( β ) R ( γ ) ,
R a = [ cos α sin α 0 sin α cos α 0 0 0 1 ] R β = [ cos β 0 sin β 0 1 0 sin β 0 cos β ] R γ = [ 1 0 0 0 cos γ sin γ 0 sin γ cos γ ] ,
R = [ cos α cos β sin α cos γ + cos α sin β sin γ sin α sin γ cos α sin β cos γ sin α cos β cos α cos γ + sin α sin β sin γ cos α sin γ sin α sin β cos γ sin β cos β sin γ cos β cos γ ] ,
{ A x + B ( y d cos ( a r c tan ( A / B ) ) ) + C = 0 , X s t a r t < X e n d A x + B ( y + d cos ( a r c tan ( A / B ) ) ) + C = 0 , X s t a r t > X e n d ,
E ( R , T ) = 1 n k = 1 n | A L S k R ( α , β , γ ) V L S k + [ T x T y T z ] T | .
R = R R k R R k 1 R R 1 T = R R k T k 1 + T T k ,

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