Generating 3D model of slope eroded gully based on photo reconstruction technique

Li Junli; Li Binbing; Liu Fangming; Li Zhanbin

doi:10.3969/j.issn.1002-6819.2015.01.018

Volume 31 Issue 1

Dec. 2014

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Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE) > 2015 > 31(1): 125-132. > DOI: 10.3969/j.issn.1002-6819.2015.01.018

Li Junli, Li Binbing, Liu Fangming, Li Zhanbin. Generating 3D model of slope eroded gully based on photo reconstruction technique[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(1): 125-132. DOI: 10.3969/j.issn.1002-6819.2015.01.018

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Generating 3D model of slope eroded gully based on photo reconstruction technique

1.
Graduate Management Group, Engineering University of CAPF, Xi'an 710086, China
2.
Department of Information Engineering, Engineering University of CAPF, Xi’an 710086, China
3.
College of Water Resources and Hydro-electric Engineering, Xi’an University of Technology, Xi’an 710048, China

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Received Date: November 28, 2014
Revised Date: December 28, 2014
Published Date: December 31, 2014

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Abstract

Abstract

Abstract: Based on Structure from Motion(SFM) and Multi-View Stereo(MVS) techniques, this paper proposed a rapid 3d reconstruction method of slope eroded gully. Firstly, feature points were extracted and described by using the Scale-Invariant Feature Transform(SIFT), and then Random Sample and Consensus(RANSAC) algorithm was applied to filter inaccurate matching points generated by Nearest Neighbor(NN) algorithm; Secondly, in the condition that there were no camera parameters and scenario-based three-dimensional information, SFM was used because it provided a solution to iterate and get camera matrix and 3d point coordinates. During the iterating process, Bundle Adjustment(BA) algorithm was used for nonlinear optimizing and to ensure symmetrical distribution of the error in order to keep precision of the reconstructed model; After that, with the constraints of local photometric consistency and global visibility, Patch-Based Multi-View Stereo(PMVS) algorithm was adopted to expand sparse point cloud generated by SFM. Thus far the dense reconstruction of point cloud had finished. In order to validate the rationality and accuracy of using this method to monitor gully erosion, indoor runoff scouring experiment was conducted in "hydrology and water resources" laboratory at Xi'an University of Technology. Photos used in the reconstruction were taken by Canon 550d SLR camera. Because modeling process relied on tracking with the oriented point on the subject to determine the final 3d model of point set, so two adjacent photos' differential seat angle can't be too large, in case of losing trace points. Reasonable selection of photo shooting location, trajectory and angle should be considered according to the experimental environment and conditions. This paper used the VisualSFM software to complete detecting and matching of feature points, sparse reconstructing of point cloud as well as self-calibrating of camera; used CMVS and PMVS2 tools to finish dense reconstruction, and Meshlab to achieve visualization. After the finish of procedures mentioned above, three-dimensional model of slope eroded gully was built. At the same time, Trimble TX5 Terrestrial Laser Scanner(TLS) was used to obtain a referential point cloud data of the eroded gully in the experiment. After the preprocessing, point clouds obtained by SFM-MVS technique and terrestrial laser scanner were segmented the same area of gully head and reduced the point number to ten thousand. Comparing reconstructed point cloud with point cloud obtained by terrestrial laser scanner and measured data showed that, dense point cloud generated by photo reconstruction method can completely show the developing form of the gully, especially can achieve a better result in the wall, ridge and rolling area than point cloud obtained by laser scanner. Calculation and analysis showed that average distance between scanned and reconstructed point cloud was 0.0034m. Respectively generated digital elevation models for two point clouds by Kriging interpolation method, and computing results indicated that the relative error of erosion estimating was 8.054%. Based on the slope map generated by DEM, characteristic lines were extracted, of which the matching rate was 89.592%. The influence of Pixel value on reconstructing process and result was discussed at the end of the paper. The results of the study provided a reference for monitoring gully erosion.
- erosion,
- computer vision,
- lasers,
- photo reconstruction,
- point cloud,
- scouring experiment

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References

[1]	Fabio R, Sabry E H. Image-based 3D Modeling: A Review[J]. The Photogrametric Record, 2006, 21(115): 269－291.
[2]	郑粉莉，王占礼，杨勤科. 我国土壤侵蚀科学研究回顾和展望[J]. 自然杂志，2008，30(1)：12－16.Zheng Fenli, Wang Zhanli, Yang Qinke. The Retrospection and Prospect on Soil Erosion Research in China[J]. Chinese Journal of Nature, 2008, 30(1): 12－16. (in Chinese with English abstract)
[3]	李占斌，朱冰冰，李鹏. 土壤侵蚀与水土保持研究进展[J]. 土壤学报，2008，45(5)：802－809.Li Zhanbin, Zhu Bingbing, Li Peng. Advancement in study on soil erosion and soil and water conservation[J]. Acta Pedologica Sinica, 2008, 45(5): 802－809. (in Chinese with English abstract)
[4]	Changchang W. VisualSFM: A Visual Structure from Motion System[EB/OL]. http://ccwu.me/vsfm/, 2011.
[5]	Longuet H. A computer algorithm for reconstructing a scene from two projections[J]. Nature, 1981, 293(10): 133－135.
[6]	Seitz S M, Curless B, Diebel J, et al. A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms[C]// IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006.
[7]	Yiehael G, Brain C, Steven M S. Multi-view Stereo Revisited[C]// IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006.
[8]	李鹏，李占斌，郑良勇. 黄土陡坡径流侵蚀产沙特性室内试验研究[J]. 农业工程学报，2005，21(7)：42－45.Li Peng, Li Zhanbin, Zheng Liangyong. Indoor experiment of characteristics of runoff erosion in loess steep slope[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2005, 21(7): 42－45. (in Chinese with English abstract)
[9]	David G L. Distinctive Image Features from Scale-InvariantKeypoints[J]. International Journal of Computer Vision, 2004, 60(2): 91－110.
[10]	Fischler M, Bolles R. Random Sampling consensus: A paradigm for model fitting with application to image analysis and automated cartography[J]. Communications of the ACM, 1981, 24(6): 381－395.
[11]	Changchang W, Sameer A, Brian C, et al. Multicore bundle adjustment[C]// IEEE Conference on Computer Vision and Pattern Recognition, 2011.
[12]	Brown D C. The bundle adjustment-progress and prospects[J]. Archives Photogrammetry, 1976, 21(3): 3－35.
[13]	方磊. 基于特征的图像序列三维场景重建技术研究[D]. 华中科技大学，2006.
[14]	戴嘉境. 基于多幅图像的三维重建理论及算法研究[D]. 上海交通大学，2012.
[15]	Yasutaka F, Curless B, Seitz S M, et al. Towards Internet-scale multi-view stereo[C]// IEEE Conference on Computer Vision and Pattern Recognition, 2010.
[16]	Yasutaka F, Jean P. Accurate, Dense, and Robust Multiview Stereopsis[C]// IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010.
[17]	Yasutaka F, Jean P. Accurate camera calibration from multi-view stereo and bundle adjustment[J]. International Journal of Computer Vision, 2009, 84(3): 257－268.
[18]	Marc P, Luc V G, Maarten V, et al. Visual modeling with a hand-held camera[J]. International Journal of Computer Vision, 2004, 59(3): 207－232.
[19]	Peter L F. Acquisition of high resolution three-dimensional models using free, open-source, photogrammetric software[J]. Palaeontologia Electronica, 2012, 15(1): 1－15.
[20]	James M R, Robson S. Straightforward reconstruction of 3D surfaces and topography with a camera: accuracy and geoscience application[J]. Journal of Geophysical Research: Earth Surface(2003－2012), 2012, 117(3): 1－17.
[21]	Westoby M J, Brasington J, Glasser N F. 'Structure- from-Motion' photogrammetry: A low-cost, effective tool for geoscience applications[J]. Geomorphology, 2012, 179(21): 300－314.
[22]	汤国安，杨昕，等. ArcGIS地理信息系统空间分析试验教程（第二版）[M]. 北京：科学出版社，2012.
[23]	李斌兵，黄磊，冯林，等. 基于点云数据的切沟泥沙负载量不确定性研究[J]. 农业工程学报，2014，30(17)：183－191.Li Binbing, Huang Lei, Feng Lin, et al. Uncertainty of gully sediment budgets based on laser point cloud data[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(17): 183－191. (in Chinese with English abstract)

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