TY - JOUR
T1 - Minimizing the adverse effects of bias and low repeatability precision in photogrammetry software through statistical analysis
AU - Napolitano, Rebecca K.
AU - Glisic, Branko
N1 - Funding Information:
We thank Wesley Reinhart for fruitful discussions. This work was supported by the Department of Civil and Environmental Engineering and the School of Engineering and Applied Sciences at Princeton. Additionally, thank you to the Sollenberger family and the Norman J. Sollenberger fund for further financial support. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1656466. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
© 2017 Elsevier Masson SAS
PY - 2018/5/1
Y1 - 2018/5/1
N2 - While photogrammetry is widely implemented in fields such as archaeology and cultural heritage, the accuracy of this method has yet to be fully addressed. It is imperative that digital photogrammetry models depicting sites of cultural heritage have accurate dimensions to avoid misunderstandings and incorrect analysis. This paper outlines a new method for minimizing the adverse effects of bias and low repeatability precision in photogrammetry software. Specifically, this paper quantitatively addresses the effects of systematic error during scaling of digital photogrammetry models as well as the random error due to a repeatability issue inherent to photogrammetry software. The method was developed using statistical analysis and robust uncertainty calculations and validated through multiple case studies.
AB - While photogrammetry is widely implemented in fields such as archaeology and cultural heritage, the accuracy of this method has yet to be fully addressed. It is imperative that digital photogrammetry models depicting sites of cultural heritage have accurate dimensions to avoid misunderstandings and incorrect analysis. This paper outlines a new method for minimizing the adverse effects of bias and low repeatability precision in photogrammetry software. Specifically, this paper quantitatively addresses the effects of systematic error during scaling of digital photogrammetry models as well as the random error due to a repeatability issue inherent to photogrammetry software. The method was developed using statistical analysis and robust uncertainty calculations and validated through multiple case studies.
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U2 - 10.1016/j.culher.2017.11.005
DO - 10.1016/j.culher.2017.11.005
M3 - Article
AN - SCOPUS:85037031974
SN - 1296-2074
VL - 31
SP - 46
EP - 52
JO - Journal of Cultural Heritage
JF - Journal of Cultural Heritage
ER -