A method to improve the accuracy of sparse UAV point cloud applied to the Amphitheater of Pompeii

Abstract

Abstract In the field of cultural heritage dissemination, the availability of an accurate 3D model is mandatory to better describe an historically relevant building and provide the user with as much information as possible. In our paper we propose a workflow to improve the accuracy of the sparse cloud (Tie Points) by means of automated mask generation on photograms acquired by UAV (Unmanned Aerial Vehicle). In the first step, the statistical distribution of reprojection errors for each image, before applying the masks, is analyzed. In the second step, masks are automatically generated for each image to exclude, in the following alignment process, parts of the image characterized by reprojection error values outside the chosen confidence interval. The BIC criterion was used to identify the probability distribution that best fits the data. The results are promising and highlight the need to implement specific processes for preparing the input data to improve the accuracy of the output 3D model. Such results are not easily achievable with the processes implemented by default in the most widely used commercial photogrammetric software.