Mesh Conflation of Oblique Photogrammetric Models Using Virtual Cameras and Truncated Signed Distance Field

Shuang Song, Rongjun Qin

Abstract: Conflating/stitching 2.5-D raster digital surface models (DSMs) into a large one has been a running practice in geoscience applications; however, conflating full-3-D mesh models, such as those from oblique photogrammetry, is extremely challenging. In this letter, we propose a novel approach to address this challenge by conflating multiple full-3-D oblique photogrammetric models into a single and seamless mesh for high-resolution site modeling. Given two or more individually collected and created photogrammetric meshes, we first propose to create a virtual camera field [with a panoramic field of view (FoV)] to incubate virtual spaces represented by truncated signed distance field (TSDF), an implicit volumetric field friendly for linear 3-D fusion; then, we adaptively leverage the truncated bound of meshes in TSDF to conflate them into a single and accurate full 3-D site model. With drone-based 3-D meshes, we show that our approach significantly improves upon traditional methods for model conflations, to drive new potentials to create excessively large and accurate full 3-D mesh models in support of geoscience and environmental applications.