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Thursday, May 7, 2020 | History

1 edition of Knowledge based building facade reconstruction from laser point clouds and images found in the catalog.

Knowledge based building facade reconstruction from laser point clouds and images

Shi Pu

Knowledge based building facade reconstruction from laser point clouds and images

by Shi Pu

  • 135 Want to read
  • 35 Currently reading

Published by Netherlands Geodetic Commission in Delft .
Written in English

    Subjects:
  • Buildings,
  • Computer simulation,
  • Image reconstruction,
  • Mathematical models,
  • Facades,
  • Three-dimensional imaging

  • Edition Notes

    StatementShi Pu
    SeriesPublications on geodesy -- 75
    Classifications
    LC ClassificationsTA1637 .P8 2010
    The Physical Object
    Paginationix, 119 p. :
    Number of Pages119
    ID Numbers
    Open LibraryOL24806762M
    ISBN 109789061323193
    LC Control Number2010501173

    Proposed Approach. In this work, we propose an automatic approach for the reconstruction of LoD-4 models, consistent with a data-driven method for geometric reconstruction of structural elements using the point cloud, and a model-driven method for the recognition of closed doors in image data based on the generalized Hough transform (Figure 1). Cited by: corresponding reconstructed building facade model. Compared to the raw TomoSAR point clouds, significantly improved elevation positioning accuracy is achieved. Finally, a first example of the reconstructed 4-D city model is presented. IndexTerms—Facade reconstruction, point cloud, TerraSAR-X, tomographic synthetic aperture radar (SAR.

    NEAREST NEIGHBOUR CLASSIFICATION ON LASER POINT CLOUDS TO GAIN OBJECT STRUCTURES FROM BUILDINGS B. Jutzi a, H. Gross b a Institute of Photogrammety and Remote Sensing, Universität Karlsruhe, Englerstr. 7, Karlsruhe, Germany @ b FGAN-FOM, Research Institute for Optronics and Pattern Recognition, Gutleuthausstraße 1, . An overview on automatic reconstruction techniques for building models from images as well as from laser scanning point clouds is given by Haala and Kada , including many approaches for the automatic reconstruction of polyhedral models with roof structures (e.g. Rottensteiner et al. ).Author: S. Tuttas, U. Stilla.

    Automatic information extraction from remote sensing images and 3D point clouds for building damage assessment. Dr. Anand Vetrivel. Knowledge based building facade reconstruction from laser point clouds and images. Dr. Shi Pu. Integrating local knowledge into GIS based flood risk assessment, Naga city, The Philippines. S. Xia and R. Wang Facade Separation in Ground-based LiDAR Point clouds based on Edges and Windows. IEEE Selected Topics in Applied Earth Observations and Remote Sensing,Volume: 12, Issue:3, March , pp, doi: /JSTARS S. Xu and R. Wang,


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Knowledge based building facade reconstruction from laser point clouds and images by Shi Pu Download PDF EPUB FB2

The latest developments of mobile laser scanning technology also make it more cost-effective to take large-scale laser scanning over urban areas. This PhD research aims at reconstructing photorealistic building facade models from terrestrial laser point clouds and close range images, with a largely automatic process.

Experiments with three data sets show that building reconstruction. This PhD research aims at reconstructing photorealistic building facade models from terrestrial laser point clouds and close range images, with a largely automatic process.

A knowledge base about building facade structures is established rst, where several important building features (wall, door, protrusion, etc.) are de ned. In the building facade reconstruction process presented in, close-range images are used for texturing the building facade models generated from terrestrial laser point clouds.

After distinguishing foreground (occlusions) laser points from background (walls) laser points by histogram analysis, the foreground laser points are projected onto close-range images so that the projected image Cited by: Knowledge based building facade reconstruction from laser point clouds and images.

By Shi Pu. Publisher: University of Twente. Year: OAI identifier: oai: Provided by: Universiteit Twente Repository. Download PDF Author: Shi Pu. This paper presents a semiautomatic building facade reconstruction approach, which efficiently combines information from terrestrial laser point clouds and close range images.

A building facade's general structure is discovered and established using the planar features from laser data. This paper presents a semiautomatic building facade reconstruction approach, which efficiently combines information from terrestrial laser point clouds and close range images.

Planar components are extracted from generated point clouds by random sample consensus and further recognized as structural components based on prior knowledge.

Windows are detected through a multi-layer complementary strategy with binary image processing techniques. Experimental results from two building facades verify the proposed by: 2.

In this paper, we propose an accurate LoD3 building reconstruction method by integrating multi-source laser point clouds and oblique remote sensing imagery. By combing high-precision plane features extracted from point clouds and accurate boundary constraint features from oblique images, the building mainframe model, which providesCited by: 2.

Via local point features, based on a clustering in hue space, the point cloud is segmented into façade-points and non-façade points. This way, the initial geometric reconstruction step Cited by: point clouds is that there is no need to derive three dimensional data from multi images using structure from motion techniques.

This paper presents a grammar-based algorithm for façade. Facades can be analyzed in 2D based on images or in 3D based on point clouds.

If high quality laser scanning point clouds are available, rectangular windows can be found quite easily: An oriented facade’s plane can be taken from a city model and then one can search for points with a significant distance to this plane, cf. (Tuttas, Stilla, ).Cited by: 2.

The advantage of the handheld laser scanner with capability of direct acquisition of very dense 3D point clouds is that there is no need to derive three dimensional data from multi images using structure from motion techniques. This paper presents a grammar-based algorithm for façade reconstruction using handheld laser scanner by: 3.

Building information models (BIMs) are maturing as a new paradigm for storing and exchanging knowledge about a facility. BIMs constructed from a CAD model do not generally capture details of a facility as it was actually by: In our reconstruction system, the algorithms used for recognizing the semantic features from.

the point cloud were developed in C/C++ on Windows, the semantic modelling framework was. developed in MAXScript on the 3DS MAX platform of Autodesk Inc., and the XBML converter. and parser were developed in Python. Reconstruction of 3D building models is still a challenging issue in 3D city modelling.

Point clouds generated from multi view images of UAV is a novel source of spatial data, which is used in this research for building by: 8. The paper describes an approach for the quality dependent reconstruction of building facades using 3D point clouds from mobile terrestrial laser scanning and coarse building models.

large holes in facades caused by occlusions, missing data, and noise from building interiors. (b)Holes are filled in a manner that maintains the 2D structure of the point cloud facilitating downstream processing.

(c)We generate high-resolution triangular meshes as. Approaches for window detection and reconstruction from TLS are often based on the assumption that windows are represented as holes in the point cloud. In Pu & Vosselman ( 9) and Boulaassal et al. () edge points of the windows are detected by searching for long triangle edges in a mesh crea ted from the point cloud.

A model-based method for building reconstruction. An integrated approach for modelling and global registration of point clouds. Automated Calibration of Fisheye Camera Systems and the Reduction of Chromatic Aberration.

Building reconstruction from images and laser scanning. ().Author: Shi Pu and George Vosselman. and validated by examples using TomoSAR point clouds generated from a stack of TerraSAR-X high-resolution spotlight images from ascending orbit covering an approximately 2-km2 high-rise area in the city of Las Vegas.

Index Terms—Clustering, facade reconstruction, point density, TerraSAR-X, tomographic SAR (TomoSAR) inversion, 4-D point cloud. Figure 1. Example for laser point clouds: a) Dense point cloud (~ points / m2) from terrestrial laser scanning.

b) sparse point cloud (~ 5 points / m2) from forward looking airborne laser scanning. Façade reconstruction methods make usually use of terrestrial laser scanning data, e.g. from a street mapper.The primary product of the laser scanning is a point cloud – a set of data points in a user defined coordinate system that represents an external surface of the measured object.

Software for pre-processing and point cloud export is usually supplied together with the scanning system. The processing of point clouds is described in section by: 4.steps are so time-consuming.

In recent years, point cloud data has been known as a valuable source for building reconstruction. The point density of stationary laser scanning in urban areas can be up to hundreds or thousands of points per square meter, which is high enough for documenting most details on building : F.

Sadeghi, H. Arefi.