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Title: Vertical orientation correction of uav image-based point clouds using statistical modeling of gable roof geometry
Authors: Polewski, P 
Yao, W 
Fang, L 
Keywords: 3D shape fitting
Gable roofs
Parameter voting
Rural area
Issue Date: 2019
Publisher: Copernicus GmbH
Source: International archives of the photogrammetry, remote sensing and spatial information sciences, 2019, v. 42, no. 2/W13, p. 519-523 How to cite?
Journal: International archives of the photogrammetry, remote sensing and spatial information sciences 
Abstract: Coregistration of point clouds obtained from various sensors is an important part of workflows for automatic building reconstruction from remote sensing data. Many approaches assume a common Z axis between the coordinate systems, and perform coregistration in 2D. While this assumption is usually valid for laser scanning (LS) data, for photogrammetric point clouds the Z axis is in general different from the world Z axis, and requires correction e.g. by manually measured ground control points (GCP). In this paper, we propose a fully automatic, GCP-free procedure for finding the world Z axis in rural areas, based on the relationships of planar surfaces in building gable roofs. Instead of performing direct gable line detection, we derive these lines as theoretical intersections between adjacent roof planes from 3D shape fitting. Each gable roof then casts a vote for both the Z axis direction and sign based on roof convexity constraints, and the votes are aggregated through a non-parametric kernel density estimator model. Experiments on two real world UAV image-based point clouds show that the Z axis recovered by our method leads to high-accuracy planimetric coregistration, with a median distance over 89 as well as 149 matched linear feature pairs (respectively for dataset 1 and 2) lying below 1 cm. Our results indicate that a high-quality vertical orientation can be achieved without using any GNSS or IMU hardware, which enables the use of low-cost UAV platforms for suburban and rural mapping tasks.
Description: 4th ISPRS Geospatial Week 2019, Netherlands, 10-14 June 2019
ISSN: 1682-1750
EISSN: 2194-9034
DOI: 10.5194/isprs-archives-XLII-2-W13-519-2019
Rights: © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
The following publication Polewski, P., Yao, W., and Fang, L.: VERTICAL ORIENTATION CORRECTION OF UAV IMAGE-BASED POINT CLOUDS USING STATISTICAL MODELING OF GABLE ROOF GEOMETRY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 519-523 is available at, 2019.
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