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Top-Down Approach to the Automatic Extraction of Individual Trees from Scanned Scene Point Cloud DataNING, X.   , TIAN, G. , WANG, Y. |
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Author keywords
computer graphics, computer aided analysis, feature extraction, object segmentation, pattern recognition
References keywords
laser(19), sensing(18), remote(18), scanning(13), mobile(13), data(13), trees(11), tree(11), point(11), photogrammetry(10)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2019-08-31
Volume 19, Issue 3, Year 2019, On page(s): 11 - 18
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.03002
Web of Science Accession Number: 000486574100002
SCOPUS ID: 85072171970
Abstract
Urban trees are essential elements in outdoor scenes recorded via terrestrial laser scanning. Although considerable interest has been centered on tree detection and reconstruction in recent years, trees cannot be easily extracted from dense and unorganized data because of the complexity and diversity of trees. In this paper, we present a top-down approach for detecting trees from point cloud data acquired for dense urban areas. Appropriate feature subsets are chosen, and then the candidate tree clusters are selected via a binary classification. After distinguishing the 3D points belonging to tree-like objects, individual trees are extracted by spectral clustering. Furthermore, a weighted constraint rule is proposed to refine the individual tree clusters. The methodology is tested on five real-world datasets that include different varieties of trees. The results reveal that most of the individual trees can be correctly detected and extracted. The results are quantitatively evaluated and reveal a global F1 value of approximately 97 percent and a precision of approximately 98 percent. Comparative analysis on the datasets is also provided to prove the effectiveness of our proposed method. |
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| [1] J. U. Duncombe, "Infrared navigation Part I: An assessment of Weinmann, M., Jutzi, B., Hinz, S., Mallet, C. "Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers". Isprs Journal of Photogrammetry and Remote Sensing. vol, 105, pp. 286-304, 2015. [CrossRef] [Web of Science Times Cited 408] [2] Li, L., Li, D., Zhu, H., Li, Y. "A dual growing method for the automatic extraction of individual trees from mobile laser scanning data". Isprs Journal of Photogrammetry and Remote Sensing. vol.120, pp.37-52, 2016. [CrossRef] [Web of Science Times Cited 58] [3] G. Vosselman, "Point cloud segmentation for urban scene classification," ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W2(7), 257-262 (2013). [CrossRef] [Web of Science Times Cited 65] [4] Jaakkola, A., Hyyppa, J., Kukko, A., Yu, X., Kaartinen, H., Lehtomaki, M., Lin, Y. "A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements". Isprs Journal of Photogrammetry and Remote Sensing. vol.65, no.6, pp.514-522, 2010. [CrossRef] [Web of Science Times Cited 268] [5] A., Bienert, S., Scheller, E. Keane, F. Mohan, and C. Nugent. "Tree detection and diameter estimations by analysis of forest terrestrial laser scanner point clouds," in ISPRS Workshop on Laser Scanning 2007 and SilvilLaser 2007, 50-55 (2012) [6] Raumonen, Kaasalainen, Mikko, Akerblom, Markku, Kaasalainen, Sanna, Kaartinen, Harri. "Fast automatic precision tree models from terrestrial laser scanner data". Remote Sensing. vol.5, no.2, pp. 491-520. 2013. [CrossRef] [Web of Science Times Cited 493] [7] Wang, Y., Weinacker, H., Koch, B. "A lidar point cloud based procedure for vertical canopy structure analysis and 3d single tree modelling in forest". Sensors. vol.8, no.6, pp. 3938-3951, 2008. [CrossRef] [Web of Science Times Cited 139] [8] B. Sirmacekand, R. Lindenbergh,"Automatic classification of trees from laser scanning point clouds," ISPRS Annals of Photogrammetry Remote Sensing and Spatial Informa II-3/W5(4), 137-144 (2015). [CrossRef] [Web of Science Times Cited 11] [9] R. C. Lindenbergh, D. Berthold, B. Sirmacek, et al., "Automated large scale parameter extraction of road-side trees sampled by a laser mobile mapping system," International Archives of the Photogrammetry Remote Sensing and S XL-3/W3, 589-594 (2015). [CrossRef] [Web of Science Times Cited 10] [10] Jutras, P., Prasher, S.O., Mehuys, G.R. "Prediction of street tree morphological parameters using artificial neural networks". Computers and Electronics in Agriculture. vol.67, no.1, pp. 9-17, 2009. [CrossRef] [Web of Science Times Cited 20] [11] Puttonen, E., Jaakkola, A., Litkey, P., Hyyppa, J. "Tree classification with fused mobile laser scanning and hyperspectral data". Sensors vol.11, no.5, pp. 5158-5182, 2011. [CrossRef] [Web of Science Times Cited 64] [12] Li, J., Hu, B., Noland, T.L. "Classification of tree species based on structural features derived from high density lidar data". Agricultural and Forest Meteorology. vol.171-172, pp. 104-114, 2013. [CrossRef] [13] Wu, B., Yu, B., Yue, W., Shu, S., Tan, W., Hu, C., Huang, Y., Wu, J., Liu, H. "A voxel-based method for automated identification and morphological parameters estimation of individual street trees from mobile laser scanning data". Remote Sensing. vol.5, no.2, pp. 584-611, 2013. [CrossRef] [Web of Science Times Cited 182] [14] Xiang, B., Yao, J., Lu, X., Li, L., Xie, R. "Segmentation-based classification for 3d urban point clouds". In: IEEE International Conference on Information and Automation. pp. 172-177, 2017. [CrossRef] [15] Barnea, S., Filin, S. "Segmentation of terrestrial laser scanning data using geometry and image information". International Journal of Photogrammetry and Remote Sensing. vol.6, no.1, pp. 33-48, 2013. [CrossRef] [Web of Science Times Cited 48] [16] Pu, S., Rutzinger, M., Vosselman, G., Elberink, S.O. "Recognizing basic structures from mobile laser scanning data for road inventory studies". Isprs Journal of Photogrammetry and Remote Sensing. vol.66, no.6, pp. S28-S39, 2011. [CrossRef] [Web of Science Times Cited 233] [17] Yang, B., Dong, Z. "A shape-based segmentation method for mobile laser scanning point clouds". Isprs Journal of Photogrammetry and Remote Sensing. vol.81, no.7, pp. 19-30, 2013. [CrossRef] [Web of Science Times Cited 158] [18] D. Munoz, J. A. Bagnell, N. Vandapel, et al., "Contextual classification with functional max-margin markov networks," in Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, 975-982 (2009). [CrossRef] [19] S. Xu, S. Xu, N. Ye, et al., "Automatic extraction of street trees non-photosynthetic components from mls data," International Journal of Applied Earth Observation and Geoinformation 69 (2018). [CrossRef] [Web of Science Times Cited 47] [20] M. Lehtomaki, A. Jaakkola, J. Hyypp, et al., "Detection of vertical pole-like objects in a road environment using vehicle-based laser scanning data," Remote Sensing 2(3), 641-664 (2010). [CrossRef] [Web of Science Times Cited 186] [21] N. H. Arachchige, "Automatic tree stem detection - a geometric feature based approach for mls point clouds," II-5/W2, 109-114 (2013). [CrossRef] [22] X. Liang, J. Hyyppa, A. Kukko, et al., "The use of a mobile laser scanning system for map- ping large forest plots," IEEE Geoscience and Remote Sensing Letters 11(9), 1504-1508 (2014). [CrossRef] [Web of Science Times Cited 104] [23] S. Xia, C. Wang, X. Pan, F.and Xi, et al., "Detecting stems in dense and homogeneous forest using single-scan tls," Forests 6(11), 3923-3945 (2015). [CrossRef] [Web of Science Times Cited 58] [24] S. Xu, N. Ye, S. Xu, et al., "A supervoxel approach to the segmentation of individual trees from lidar point clouds," Remote Sensing Letters 9(6), 515-523 (2018). [CrossRef] [Web of Science Times Cited 28] [25] Hyyppa, J., Kelle, O., Lehikoinen, M., Inkinen, M. "A segmentation-based method to retrieve stem volume estimates from 3-d tree height models produced by laser scanners". vol.39, no.5, pp. 969-975, 2001. [CrossRef] [Web of Science Times Cited 534] [26] Lalonde, J.F., Vandapel, N., Huber, D.F., Hebert, M. "Natural terrain classification using three dimensional ladar data for ground robot mobility". Journal of Field Robotics. vol. 23, no.10, pp. 839-861, 2006. [CrossRef] [Web of Science Times Cited 316] [27] Rutzinger, M., Pratihast, A.K., Elberink, S.J.O., Vosselman, G. "Tree modelling from mobile laser scanning datasets". Photogrammetric Record. Vol.26, no.135, pp.361-372. 2011. [CrossRef] [Web of Science Times Cited 58] [28] F. Monnier, B. Vallet, and B. Soheilian, "Trees detection from laser point clouds acquired in dense urban areas by a mobile mapping system," in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXII ISPRS Congress, I-3(I-3) (2012). [CrossRef] [29] W. Yao and H. Fan, "Automated detection of 3d individual trees along urban road corridors by mobile laser scanning systems," in International Symposium on Mobile Mapping Technology, (2013). [30] Zhong, R., Wei, J., Su, W., Chen, Y.F. "A method for extracting trees from vehicle-borne laser scanning data". Mathematical and Computer Modelling. vol.58, no.3-4, pp. 727-736, 2013. [CrossRef] [Web of Science Times Cited 27] [31] P. Raumonen, M. Kaasalainen, M. Kerblom,et al., "Fast automatic precision tree models from terrestrial laser scanner data," Remote Sensing 5(2), 491-520 (2013). [CrossRef] [Web of Science Times Cited 493] [32] W. Fan, W. Chenglu, L. Jonathan, et al., "Automated extraction of urban trees from mobile lidar point clouds," in Isprs International Conference on Computer Vision in Remote Sensing, 99010P (2016). [CrossRef] [Web of Science Times Cited 10] [33] Zhong L., Cheng, L., Xu, H., Wu, Y., Chen, Y., Li, M. "Segmentation of individual trees from tls and mls data," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10(2), 774-787 (2017). [CrossRef] [Web of Science Times Cited 76] [34] J. Trochta, M. Krucek, T. Vrska, et al., "3d forest: An application for descriptions of three- dimensional forest structures using terrestrial lidar," Plos One 12(5), e0176871 (2017). 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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
