EVALUATION OF PHOTOGRAMMETRIC BLOCK ORIENTATION USING QUALITY DESCRIPTORS FROM STATISTICALLY FILTERED TIE POINTS

Due to the increasing number of low-cost sensors, widely accessible on the market, and because of the supposed granted correctness of the semi-automatic workflow for 3D reconstruction, highly implemented in the recent commercial software, more and more users operate nowadays without following the rigorousness of classical photogrammetric methods. This behaviour often naively leads to 3D products that lacks metric quality assessment. This paper proposes and analyses an approach that gives the users the possibility to preserve the trustworthiness of the metric information inherent in the 3D model, without sacrificing the automation offered by modern photogrammetry software. At the beginning, the importance of Data Quality Assessment is outlined, together with some recall of photogrammetry best practices. With the purpose of guiding the user through a correct pipeline for a certified 3D model reconstruction, an operative workflow is proposed, focusing on the first part of the object reconstruction steps (tie-points extraction, camera calibration, and relative orientation). A new GUI (Graphical User Interface) developed for the open source MicMac suite is then presented, and a sample dataset is used for the evaluation of the photogrammetric block orientation using statistically obtained quality descriptors. The results and the future directions are then presented and discussed.