XXII ISPRS Congress 2012: Technical Commission VII

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Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/7, III/2, V/1, V/3, ICWG V/I: LOW-COST UAVS (UVSS) AND MOBILE MAPPING SYSTEMS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: AN ACCURACY ASSESSMENT OF GEOREFERENCED POINT CLOUDS PRODUCED VIA MULTI-VIEW STEREO TECHNIQUES APPLIED TO IMAGERY ACQUIRED VIA UNMANNED AERIAL VEHICLE Steve Harwin and Arko Lucieer

Document type:: Multivolume work

Structure type:: Chapter

nd robust d of this he video ire points tracking M on still efore, the of this ints from procedure ator have : matched rientation stained in GPS and method is d method orm more rol points, Therefore, v altitude that have r mapping spectives. nsing and ISPRS rientation ngs of the XXXVIII, ym scale- er Vision, ol, 2008. ision and 6--359 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia AN ACCURACY ASSESSMENT OF GEOREFERENCED POINT CLOUDS PRODUCED VIA MULTI-VIEW STEREO TECHNIQUES APPLIED TO IMAGERY ACQUIRED VIA UNMANNED AERIAL VEHICLE Steve Harwin and Arko Lucieer School of Geography and Environmental Studies University of Tasmania Private Bag 76, Hobart, Australia 7001 Stephen.Harwin Q utas.edu.au KEY WORDS: Point Cloud, Accuracy, Reference Data, Surface, Georeferencing, Bundle, Reconstruction, Photogrammetry ABSTRACT: Low-cost Unmanned Aerial Vehicles (UAVs) are becoming viable environmental remote sensing tools. Sensor and battery technology is expanding the data capture opportunities. The UAV, as a close range remote sensing platform, can capture high resolution photog- raphy on-demand. This imagery can be used to produce dense point clouds using multi-view stereopsis techniques (MVS) combining computer vision and photogrammetry. This study examines point clouds produced using MVS techniques applied to UAV and terrestrial photography. A multi-rotor micro UAV acquired aerial imagery from a altitude of approximately 30-40 m. The point clouds produced are extremely dense («1-3 cm point spacing) and provide a detailed record of the surface in the study area, a 70 m section of sheltered coastline in southeast Tasmania. Areas with little surface texture were not well captured, similarly, areas with complex geometry such as grass tussocks and woody scrub were not well mapped. The process fails to penetrate vegetation, but extracts very detailed terrain in unvegetated areas. Initially the point clouds are in an arbitrary coordinate system and need to be georeferenced. A Helmert transfor- mation is applied based on matching ground control points (GCPs) identified in the point clouds to GCPs surveying with differential GPS. These point clouds can be used, alongside laser scanning and more traditional techniques, to provide very detailed and precise representations of a range of landscapes at key moments. There are many potential applications for the UAV-MVS technique, including coastal erosion and accretion monitoring, mine surveying and other environmental monitoring applications. For the generated point clouds to be used in spatial applications they need to be converted to surface models that reduce dataset size without loosing too much detail. Triangulated meshes are one option, another is Poisson Surface Reconstruction. This latter option makes use of point normal data and produces a surface representation at greater detail than previously obtainable. This study will visualise and compare the two surface representations by comparing clouds created from terrestrial MVS (T-MVS) and UAV-MVS. 1 INTRODUCTION Terrain and Earth surface representations were traditionally de- rived from imagery using analogue photogrammetric techniques that produced contours and topological maps from stereo pairs. Digital photogrammetry has sought ways to automate the process and improve efficiency. Modern mesh or grid based representa- tions provide relatively efficient storage of terrain data at a wide range of resolutions. The quality of these representations is de- pendent on the techniques used for data capture and processing. The representation improves with resolution and the data capture technique must be able to accurately determine height points at sufficient density to portray the shape of the surface. The diffi- culty faced is that the storage and visualisation become increas- ingly difficult as resolution increases. The surface must there- fore be represented by an approximation that resembles reality as closely as possible. In recent decades photogrammetric techniques have sought to im- prove surface representation through automated feature extrac- tion and matching. Computer vision uses Structure from Mo- tion (SfM) to achieve similar outputs. SfM incorporates multi- view stereopsis (MVS) techniques that match features in multi- ple views of a scene and derive 3D model coordinates and cam- era position and orientation. The Scale Invariant Feature Trans- form (SIFT) operator (Lowe, 2004) provides a robust description of features in a scene and allows features distinguished in other views to be compared and matched. A bundle adjustment can then be used to derive a set of 3D coordinates of matched features. The point density is proportional to the number of matched fea- tures and untextured surfaces, occlusions, illumination changes 475 and acquisition geometry can result in fewer matches (Remondino and El-Hakim, 2006). The Bundler software! is an open source tool for performing least squares bundle adjustment (Snavely et al., 2006). To reduce computing overheads imagery is often down sampled. Typically the next stage is to densify the point cloud us- ing MVS techniques, such as the patch-based multi-view stereo software PMVS2 ?. Each point in the resulting cloud has an asso- ciated normal. The point clouds produced from UAV imagery (re- ferred to as UAV-MVS) acquired at 30-50 m flying height above ground level (AGL) have a density of 1-3 points per cm?. There can be in excess of 7 million points in a cloud (file size of 500 Mb). The point cloud generated can be georeferenced by matching control points in the cloud to surveyed ground control points (GCPs). The resulting accuracy is dependent on the accuracy of the GCP survey or reference datasets and in this case it is approximately 25-40 mm (Harwin and Lucieer, 2012). The accuracy can be im- proved with coregistration to a more accurate base dataset. To allow these large datasets to be used it is usually necessary to convert them into a more storage efficient data structure so that the data can be used in conventional GIS and 3D visuali- sation software that rely on a surface for texturing rather than a point cloud. Grid based (or Raster) and triangular mesh based data models, such as Digital Surface Models (DSMs) and Trian- gular Irregular Networks (TINs), are commonly used. After pro- cessing and classification a Digital Elevation Model (DEM) or a Digital Terrain Model (DTM) representation of the earth’s sur- face, without any vegetation or man-made structures, can be de- Lhttp://phototour.cs.washington.edu/bundler/ ?http://grail.cs.washington.edu/software/pmvs/

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