Panorama Image Sets for Terrestrial Photogrammetric Surveys

Abstract. High resolution 3D models produced from photographs acquired with consumer-grade cameras are becoming increasingly common in the fields of geosciences. However, the quality of an image-based 3D model depends on the planning of the photogrammetric surveys. This means that the geometric configuration of the multi-view camera network and the control data have to be designed in accordance with the required accuracy, resolution and completeness. From a practical application point of view, a proper planning (of both photos and control data) of the photogrammetric survey especially for terrestrial acquisition, is not always ensured due to limited accessibility of the target object and the presence of occlusions. To solve these problems, we propose a different image acquisition strategy and we test different geo-referencing scenarios to deal with the practical issues of a terrestrial photogrammetric survey. The proposed photogrammetric survey procedure is based on the acquisition of a sequence of images in panorama mode by rotating the camera on a standard tripod. The offset of the pivot point from the projection center prevents the stitching of these images into a panorama. We demonstrate how to still take advantage of this capturing mode. The geo-referencing investigation consists of testing the use of directly observed coordinates of the camera positions, different ground control point (GCP) configurations, and GCPs with different accuracies, i.e. artificial targets vs. natural features. Images of the test field in a low-slope hill were acquired from the ground using an SLR camera. To validate the photogrammetric results a terrestrial laser scanner survey is used as benchmark.

[1]  G. Vosselman,et al.  Robust extraction of image correspondences exploiting the image scene geometry and approximate camera orientation , 2013 .

[2]  Philippe De Smedt,et al.  Towards a three-dimensional cost-effective registration of the archaeological heritage , 2013 .

[3]  Mark W. Smith,et al.  From experimental plots to experimental landscapes: topography, erosion and deposition in sub‐humid badlands from Structure‐from‐Motion photogrammetry , 2015 .

[4]  S. Robson,et al.  Mitigating systematic error in topographic models derived from UAV and ground‐based image networks , 2014 .

[5]  S. Robson,et al.  Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application , 2012 .

[6]  Samuel T. Thiele,et al.  Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology , 2014 .

[7]  C. Fraser,et al.  Digital camera calibration methods: Considerations and comparisons , 2006 .

[8]  Dieter Fritsch,et al.  IMAGE ACQUISITION AND MODEL SELECTION FOR MULTI-VIEW STEREO , 2013 .

[9]  Norbert Pfeifer,et al.  ORIENTAL - AUTOMATIC GEO-REFERENCING AND ORTHO-RECTIFICATION OF ARCHAEOLOGICAL AERIAL PHOTOGRAPHS , 2013 .

[10]  Klaus Thoeni,et al.  A COMPARISON OF MULTI-VIEW 3D RECONSTRUCTION OF A ROCK WALL USING SEVERAL CAMERAS AND A LASER SCANNER , 2014 .

[11]  J. Dietrich.  Riverscape mapping with helicopter-based Structure-from-Motion photogrammetry , 2016 .

[12]  N. Pfeifer,et al.  A Correspondence Framework for ALS Strip Adjustments based on Variants of the ICP Algorithm , 2015 .

[13]  Natan Micheletti,et al.  Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone , 2015 .

[14]  P. Allemand,et al.  Ground-based multi-view photogrammetry for the monitoring of landslide deformation and erosion , 2015 .

[15]  M. Rothermel,et al.  SURE : PHOTOGRAMMETRIC SURFACE RECONSTRUCTION FROM IMAGER Y , 2013 .

[16]  Alberto Guarnieri,et al.  Use of terrestrial photogrammetry based on structure‐from‐motion for mass balance estimation of a small glacier in the Italian alps , 2015 .

[17]  Fabio Menna,et al.  ACCURACY OF TYPICAL PHOTOGRAMMETRIC NETWORKS IN CULTURAL HERITAGE 3D MODELING PROJECTS , 2014 .

[18]  Horst Bischof,et al.  Automated End-to-End Workflow for Precise and Geo-accurate Reconstructions using Fiducial Markers , 2014 .

[19]  Menna,et al.  ACCURACY AND BLOCK DEFORMATION ANALYSIS IN AUTOMATIC UAV AND TERRESTRIAL PHOTOGRAMMETRY – LESSON LEARNT – , 2013 .

[20]  Gianfranco Forlani,et al.  Production of high-resolution digital terrain models in mountain regions to support risk assessment , 2015 .

[21]  J. Chandler,et al.  Minimising systematic error surfaces in digital elevation models using oblique convergent imagery , 2011 .