15 February 2017 Reconstruction of measurable three-dimensional point cloud model based on large-scene archaeological excavation sites
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Abstract
This paper outlines a low-cost, user-friendly photogrammetric technique with nonmetric cameras to obtain excavation site digital sequence images, based on photogrammetry and computer vision. Digital camera calibration, automatic aerial triangulation, image feature extraction, image sequence matching, and dense digital differential rectification are used, combined with a certain number of global control points of the excavation site, to reconstruct the high precision of measured three-dimensional (3-D) models. Using the acrobatic figurines in the Qin Shi Huang mausoleum excavation as an example, our method solves the problems of little base-to-height ratio, high inclination, unstable altitudes, and significant ground elevation changes affecting image matching. Compared to 3-D laser scanning, the 3-D color point cloud obtained by this method can maintain the same visual result and has advantages of low project cost, simple data processing, and high accuracy. Structure-from-motion (SfM) is often used to reconstruct 3-D models of large scenes and has lower accuracy if it is a reconstructed 3-D model of a small scene at close range. Results indicate that this method quickly achieves 3-D reconstruction of large archaeological sites and produces heritage site distribution of orthophotos providing a scientific basis for accurate location of cultural relics, archaeological excavations, investigation, and site protection planning. This proposed method has a comprehensive application value.
© 2017 SPIE and IS&T
Chun-Sen Zhang, Chun-Sen Zhang, Meng-Meng Zhang, Meng-Meng Zhang, Wei-Xing Zhang, Wei-Xing Zhang, } "Reconstruction of measurable three-dimensional point cloud model based on large-scene archaeological excavation sites," Journal of Electronic Imaging 26(1), 011027 (15 February 2017). https://doi.org/10.1117/1.JEI.26.1.011027 . Submission: Received: 1 July 2016; Accepted: 23 January 2017
Received: 1 July 2016; Accepted: 23 January 2017; Published: 15 February 2017
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