Assessing geoaccuracy of structure from motion point clouds from long-range image collections

Automatically extracted and accurate scene structure generated from airborne platforms is a goal of many applications in the photogrammetry, remote sensing, and computer vision fields. This structure has traditionally been extracted automatically through the structure-from-motion (SfM) workflows. Although this process is very powerful, the analysis of error in accuracy can prove difficult. Our work presents a method of analyzing the georegistration error from SfM derived point clouds that have been transformed to a fixed Earth-based coordinate system. The error analysis is performed using synthetic airborne imagery which provides absolute truth for the ray-surface intersection of every pixel in every image. Three methods of georegistration are assessed; (1) using global positioning system (GPS) camera centers, (2) using pose information directly from on-board navigational instrumentation, and (3) using a recently developed method that utilizes the forward projection function and SfM-derived camera pose estimates. It was found that the georegistration derived from GPS camera centers and the direct use of pose information from on-board navigational instruments is very sensitive to noise from both the SfM process and instrumentation. The georegistration transform computed using the forward projection function and the derived pose estimates prove to be far more robust to these errors. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)