Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4/W5, 171-176, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-4-W5/171/2015/
doi:10.5194/isprsarchives-XL-4-W5-171-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
11 May 2015
AN AUTOMATIC 3D RECONSTRUCTION METHOD BASED ON MULTI-VIEW STEREO VISION FOR THE MOGAO GROTTOES
J. Xiong, S. Zhong, and L. Zheng School of Electronic Information, Wuhan University, Wuhan, Hubei 430072, China
Keywords: 3D Reconstruction, Multi-view vision, Epipolar Constraint, Correlation, Texture mapping, Mogao Grottoes Abstract. This paper presents an automatic three-dimensional reconstruction method based on multi-view stereo vision for the Mogao Grottoes. 3D digitization technique has been used in cultural heritage conservation and replication over the past decade, especially the methods based on binocular stereo vision. However, mismatched points are inevitable in traditional binocular stereo matching due to repeatable or similar features of binocular images. In order to reduce the probability of mismatching greatly and improve the measure precision, a portable four-camera photographic measurement system is used for 3D modelling of a scene. Four cameras of the measurement system form six binocular systems with baselines of different lengths to add extra matching constraints and offer multiple measurements. Matching error based on epipolar constraint is introduced to remove the mismatched points. Finally, an accurate point cloud can be generated by multi-images matching and sub-pixel interpolation. Delaunay triangulation and texture mapping are performed to obtain the 3D model of a scene. The method has been tested on 3D reconstruction several scenes of the Mogao Grottoes and good results verify the effectiveness of the method.
Conference paper (PDF, 2670 KB)


Citation: Xiong, J., Zhong, S., and Zheng, L.: AN AUTOMATIC 3D RECONSTRUCTION METHOD BASED ON MULTI-VIEW STEREO VISION FOR THE MOGAO GROTTOES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4/W5, 171-176, doi:10.5194/isprsarchives-XL-4-W5-171-2015, 2015.

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