An examination of the traceability and dependability of the virtualisation properties is prompted by the widespread use of three-dimensional models. The challenge of obtaining accuracy indicators directly from the photogrammetric method when a reference model is missing is widely acknowledged. In this study, a robust method based on a statistical analysis of the uncertainty associated with Tie Points (TPs) is presented to provide a strict framework for the informed processing of photogrammetric survey data. In the phases of Structure estimation, Structure optimisation, and Dense Cloud generation, the key steps and variables affecting data processing are described. The workflow is then applied to a specific bronze museum finding smaller than 20 cm in size. All tie points that overcome the filtering phase are included in the procedure and for their coordinates the covariance matrix is examined. The error ellipsoid is calculated and the distribution of the lengths of the major semi-axes is analysed to calculate an appropriate tolerance interval which can be used as an indicator of the accuracy of the entire photogrammetric process. Indeed, using the tolerance intervals tool allows for the derivation of a representative indicator that can be compared with the outcomes of other photogrammetric processes while overcoming the ambiguity of statistical indicators that are not representative in the case of a non-normal distribution.

A STATISTICAL ANALYSIS FOR THE ASSESSMENT OF CLOSE-RANGE PHOTOGRAMMETRY GEOMETRICAL FEATURES

di Filippo, A.
;
Antinozzi, S.
;
Sanseverino, A.
2022-01-01

Abstract

An examination of the traceability and dependability of the virtualisation properties is prompted by the widespread use of three-dimensional models. The challenge of obtaining accuracy indicators directly from the photogrammetric method when a reference model is missing is widely acknowledged. In this study, a robust method based on a statistical analysis of the uncertainty associated with Tie Points (TPs) is presented to provide a strict framework for the informed processing of photogrammetric survey data. In the phases of Structure estimation, Structure optimisation, and Dense Cloud generation, the key steps and variables affecting data processing are described. The workflow is then applied to a specific bronze museum finding smaller than 20 cm in size. All tie points that overcome the filtering phase are included in the procedure and for their coordinates the covariance matrix is examined. The error ellipsoid is calculated and the distribution of the lengths of the major semi-axes is analysed to calculate an appropriate tolerance interval which can be used as an indicator of the accuracy of the entire photogrammetric process. Indeed, using the tolerance intervals tool allows for the derivation of a representative indicator that can be compared with the outcomes of other photogrammetric processes while overcoming the ambiguity of statistical indicators that are not representative in the case of a non-normal distribution.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4815932
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