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Title: Hierarchical regularization of polygons for photogrammetric point clouds of oblique images
Authors: Xie, L 
Hu, H 
Zhu, Q
Wu, B 
Zhang, Y
Issue Date: 2017
Source: International archives of the photogrammetry, remote sensing and spatial information sciences, 2017, v. XLII-1/W1, p. 35-40
Abstract: Despite the success of multi-view stereo (MVS) reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.
Keywords: 2D polygon regularization
Global optimization
Normal reconstruction
Publisher: Copernicus GmbH
Journal: International archives of the photogrammetry, remote sensing and spatial information sciences 
ISSN: 1682-1750
DOI: 10.5194/isprs-archives-XLII-1-W1-35-2017
Description: ISPRS Hannover Workshop 2017 on High-Resolution Earth Imaging for Geospatial Information, HRIGI 2017, City Models, Roads and Traffic , CMRT 2017, Image Sequence Analysis, ISA 2017, European Calibration and Orientation Workshop, EuroCOW 2017, 6 - 9 June 2017, Hannover, Germany
Rights: © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License (https://creativecommons.org/licenses/by/3.0/).
The following publication Xie, L., Hu, H., Zhu, Q., Wu, B., and Zhang, Y.: HIERARCHICAL REGULARIZATION OF POLYGONS FOR PHOTOGRAMMETRIC POINT CLOUDS OF OBLIQUE IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1/W1, 35–40 is available at https://doi.org/10.5194/isprs-archives-XLII-1-W1-35-2017, 2017
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