Mapping field photographs to textured surface meshes directly on mobile devices

Abstract

The mapping of photographs to surface geometry is an important procedure for many applications within the geosciences. This paper proposes an interactive framework for feature-based image-to-geometry mapping that works directly on mobile devices, under challenging imaging conditions and with limited available hardware performance. The framework makes use of openly available digital elevation models (DEMs) together with mobile position-and-orientation sensor data. It integrates calculation heuristics for result evaluation and feedback, synthesising available knowledge in current registration literature. The approach is assessed on two image datasets captured on separate occasions. Their interpretations are mapped to one textured lidar surface model and the projection accuracy is qualitatively assessed. The experiments show a significant accuracy improvement in photograph registration results, as well as the faithful mapping of image interpretations on the underlying surface geometry. This semi-automatic, user-guided, interactive approach is superior to comparable fully automatic registration methods.

LIME: Software for 3-D visualization, interpretation, and communication of virtual geoscience models

“…Laser scanning (lidar), global navigation satellite systems (GNSS), digital photogrammetry (also referred to as structure from motion [SfM]), and imaging remote sensing have all evolved heavily over the last two decades, and are distinguished by unprecedented resolution, precision, and ease of use. Computing hardware has developed to facilitate field-based acquisition (Weng et al, 2012;Kehl et al, 2017), and more analysis tools are available in geographical information systems (GIS). The evolving state of the art can be followed through the scientific literature, from early adoption to the status quo.…”

“…The evolving state of the art can be followed through the scientific literature, from early adoption to the status quo. This is exemplified by rapid adoption across the many arms of the geoscience subdisciplines (see, e.g., McCaffrey et al [2005], Pringle et al [2006], Buckley et al [2008a], Kääb [2008], Pavlis et al [2010], Jaboyedoff et al [2012], Hodgetts [2013], Bemis et al [2014], Eitel et al [2016], Eltner et al [2016], Kehl et al [2017], and Squelch [2017] as a small subset of papers providing snapshots of developments through time).…”

Using digital field notebooks in geoscientific learning in polar environments

“…Finally, we consider the need to take virtual outcrop models to the field in the future, and preferably be able to directly include new observations. Kehl et al (2017) outline some possibilities of offline mapping of photographs onto textured surfaces directly on mobile devices. This software is, however, not available on iOS.…”