University of Twente Student Theses


Mobile Mapping by integrating Structure from Motion approach with Global Navigation Satellite System

Jariwala, Jayson Jayeshkumar (2013) Mobile Mapping by integrating Structure from Motion approach with Global Navigation Satellite System.

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Abstract:Over the past few years, there is an emerging growth in mobile mapping systems which can effectively capture the geospatial data in an efficient way. A typical terrestrial mobile mapping system consists of camera, laser scanners, GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System). Imagery data is captured by camera and the point clouds are acquired by the laser scanners. GNSS and INS are used for measuring the positional and orientation information of the mapping sensors respectively to achieve direct geo-referencing. GNSS/INS system is very expensive which makes the overall mapping system very expensive. An alternative to make this system is to use Structure from Motion Approach (SfM), to minimize the relative cost of this system. SfM generates 3D point clouds of scene and estimate the orientation parameter for mapping sensor by using imagery data. The major issue with SfM is that it generates point clouds in arbitrary coordinate system with arbitrary scale. In this research work, the feasibility of mapping by integration of the structure from motion approach and GNSS was assessed to generate geo-referenced point clouds. In the first step, sequences of images were captured by measuring the exposure station positions. Then feature extractions and matching were done on the sequence of overlapping images. Bundle adjustment was then applied on it to generate the 3D scene (point clouds) of rigid body and for estimation of camera orientation parameters. The generated point clouds were in arbitrary coordinate system, so tie points were selected to transform into mapping coordinate system. Space photo intersection was applied on tie points with the use of exposure orientation parameters and matched feature points in sequence of overlapping images to transform into world coordinate system. Further, point-based similarity transformation was used to generate transformation parameters from tie points. These transformation parameters were applied on whole generated point cloud to transform it into world coordinate system with proper scale. Then the accuracy assessments on point cloud were carried out using internal and external accuracy assessment. Sometime the epipolar lines do not exactly cross at a fixed point in different overlapping images due to which a distorted 3D scene (point clouds) was created. There was an error in the estimation of orientation parameters due to no ground measurements were used in bundle adjustment. Thus it was observed that the shape of the point cloud was concaved near start and end edges of the scene. RMSE were 32.21 cm, 20.50 cm and 23.56 cm in easting, northing (depth) and height respectively. Keywords: Mobile Mapping, Terrestrial Photogrammetry, Structure from Motion, Global Navigation Satellite System, Feature extraction, Feature matching, Space photo intersection, 3D similarity transformation.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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