Abstract
Adding supplementary texture and 2D image-based annotations to 3D surface models is a useful next step for domain specialists to make use of photorealistic products of laser scanning and photogrammetry. This requires a registration between the new camera imagery and the model geometry to be solved, which can be a time-consuming task without appropriate automation. The increasing availability of photorealistic models, coupled with the proliferation of mobile devices, gives users the possibility to complement their models in real time. Modern mobile devices deliver digital photographs of increasing quality, as well as on-board sensor data, which can be used as input for practical and automatic camera registration procedures. Their familiar user interface also improves manual registration procedures. This paper introduces a fully automatic pose estimation method using the on-board sensor data for initial exterior orientation, and feature matching between an acquired photograph and a synthesised rendering of the orientated 3D scene as input for fine alignment. The paper also introduces a user-friendly manual camera registration- and pose estimation interface for mobile devices, based on existing surface geometry and numerical optimisation methods. The article further assesses the automatic algorithm’s accuracy compared to traditional methods, and the impact of computational- and environmental parameters. Experiments using urban and geological case studies show a significant sensitivity of the automatic procedure to the quality of the initial mobile sensor values. Changing natural lighting conditions remain a challenge for automatic pose estimation techniques, although progress is presented here. Finally, the automatically-registered mobile images are used as the basis for adding user annotations to the input textured model.
Highlights
Textured surface models are used in a widening range of application domains, such a urban planning (Semmo and Dollner, 2015), cultural heritage (Potenziani et al, 2015), archaeology (Van Damme, 2015) and geological outcrop modelling (Howell et al, 2014, Rarity et al, 2014)
This paper introduces a fully automatic pose estimation method using the on-board sensor data for initial exterior orientation, and feature matching between an acquired photograph and a synthesised rendering of the orientated 3D scene as input for fine alignment
This paper presents an extension to automatic Image-toGeometry procedures using the in-built sensor data from mobile devices, as well as a novel approach for manual registration, taking the perceptual challenges into account, as a robust automation backup
Summary
Textured surface models are used in a widening range of application domains, such a urban planning (Semmo and Dollner, 2015), cultural heritage (Potenziani et al, 2015), archaeology (Van Damme, 2015) and geological outcrop modelling (Howell et al, 2014, Rarity et al, 2014). After a model has been captured, often by means of terrestrial laser scanning (TLS) or photogrammetry, it may be desirable for domain experts to supplement the model with novel images to make initially-hidden features visible, or to add annotations. Retexturing models, introducing supplementary textures, or annotating (i.e. interpreting, mapping) 3D structures in novel 2D images is based on retrieving accurate exterior orientations using Image-to-Geometry registration. Available tools to obtain the pose of a captured image commonly rely on complex, time-consuming, perceptually challenging and errorprone manual 2D-3D registration methods. This leads to a bottleneck in geoscientific workflows
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