Method of engineering volume monitoring and calculation for open-pit mine from UAV images

Dongbei Daxue Xuebao/Journal of Northeastern University

Volumn 37, Issue 1, 2016, Pages 84-88

  Xu, Zhi Hua ^a   Wu, Li Xin ^b,c   Chen, Shao Jie ^d   Wang, Zhi ^b  

^a BEIJING NORMAL UNIVERSITY   (China)

^b NORTHEASTERN UNIVERSITY   (China)

^c CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^d LONGYAN UNIVERSITY   (China)

Author keywords

Engineering volume; Open pit mine; Patch based multi view stereo (PMVS); Structure from motion (SfM); Unmanned aerial vehicle (UAV)

Indexed keywords

GEOMETRICAL OPTICS; IMAGE SEGMENTATION; UNMANNED AERIAL VEHICLES (UAV);

AUTOMATICALLY GENERATED; DIFFERENTIAL METHODS; DIGITAL TERRAIN MODEL; MULTI-VIEW STEREO; REGISTRATION METHODS; STRUCTURE FROM MOTION; TERRESTRIAL LASER SCANNING; TRIANGULATED IRREGULAR NETWORKS;

OPEN PIT MINING;

EID: 84975733500     PISSN: 10053026     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1005-3026.2016.01.018     Document Type: Article

References (14)

1. Chen Yong-feng, Wu Xiao-ru, Yuan Yu-bo. Research of mining engineering volume calculation method based on DTM for surface mine[J]. Metal Mine, 2010, 12(1): 15-18.
2. Grohmann C H, Sawakuchi A O. Influence of cell size on volume calculation using digital terrain model: a case of coastal dune fields[J]. Geomorphology, 2013, 180/181: 130-136.
3. Liu X F, Chen P, Tong X H, et al. UAV-based low-altitude aerial photogrammetric application in mine areas measurement[C] // Second International Workshop on Earth Observation and Remote Sensing Applications. Shanghai, 2012: 240-242.
4. McLeod T, Samson C, Labrie M, et al. Using video acquired from an unmanned aerial vehicle (UAV) to measure fracture orientation in an open-pit mine[J]. Geomatica, 2013, 67(3): 173-180.
5. Snavely N. Scene reconstruction and visualization from Internet photo collections[D]. Seattle: University of Washington, 2009.
6. Lowe D. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2): 91-110.
7. Bay H, Tuytelaars T, Van Gool L. SURF: speeded up robust features[C] // The 9th European Conference on Computer Vision. Graz, 2006: 404-417.
8. Feiner S, Macintyre B, Höllerer T, et al. A touring machine: prototyping 3D mobile augmented reality systems for exploring the urban environment[J]. Personal Technologies, 1997, 4(1): 208-217.
9. Hartley R I. In defense of the eight-point algorithm[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(6): 580-593.
10. Lourakis M, Argyros A. The design and implementation of a generic sparse bundle adjustment software package based on the Levenberg-Marquardt algorithm[R]. Heraklion: Institute of Computer Science, Foundation for Research and Technology-Hellas, 2004.
11. Furukawa Y, Ponce J. Accurate, dense, and robust multi-view stereopsis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(8): 1362-1376.
12. Besl P J, McKay N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(2): 239-256.
13. Pulli K. Multiview registration for large data sets[C] // 3-D Digital Imaging and Modeling. Ottawa, 1999: 160-168.
14. Shen Yong-lin, Liu Jun, Wu Li-xin, et al. Reconstruction of disaster scene from UAV images and flight-control data[J]. Geography and Geo-Information Science. 2011, 27(6): 13-17.