A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs

In this paper, a novel framework of the 3D reconstruction of buildings is proposed, focusing on remote sensing super-generalized stereo-pairs (SGSPs). As we all know, 3D reconstruction cannot be well performed using nonstandard stereo pairs, since reliable stereo matching could not be achieved when...

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Main Authors: Yiming Yan, Nan Su, Chunhui Zhao, Liguo Wang
Format: Article
Language:English
Published: MDPI AG 2017-09-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/17/9/2153
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spelling doaj-c2eadac7d01a4e4d9533b299bde18dd72020-11-24T21:25:09ZengMDPI AGSensors1424-82202017-09-01179215310.3390/s17092153s17092153A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-PairsYiming Yan0Nan Su1Chunhui Zhao2Liguo Wang3Department of information and communication engineering, Harbin Engineering University, Harbin 150001, ChinaDepartment of information and communication engineering, Harbin Engineering University, Harbin 150001, ChinaDepartment of information and communication engineering, Harbin Engineering University, Harbin 150001, ChinaDepartment of information and communication engineering, Harbin Engineering University, Harbin 150001, ChinaIn this paper, a novel framework of the 3D reconstruction of buildings is proposed, focusing on remote sensing super-generalized stereo-pairs (SGSPs). As we all know, 3D reconstruction cannot be well performed using nonstandard stereo pairs, since reliable stereo matching could not be achieved when the image-pairs are collected at a great difference of views, and we always failed to obtain dense 3D points for regions of buildings, and cannot do further 3D shape reconstruction. We defined SGSPs as two or more optical images collected in less constrained views but covering the same buildings. It is even more difficult to reconstruct the 3D shape of a building by SGSPs using traditional frameworks. As a result, a dynamic multi-projection-contour approximating (DMPCA) framework was introduced for SGSP-based 3D reconstruction. The key idea is that we do an optimization to find a group of parameters of a simulated 3D model and use a binary feature-image that minimizes the total differences between projection-contours of the building in the SGSPs and that in the simulated 3D model. Then, the simulated 3D model, defined by the group of parameters, could approximate the actual 3D shape of the building. Certain parameterized 3D basic-unit-models of typical buildings were designed, and a simulated projection system was established to obtain a simulated projection-contour in different views. Moreover, the artificial bee colony algorithm was employed to solve the optimization. With SGSPs collected by the satellite and our unmanned aerial vehicle, the DMPCA framework was verified by a group of experiments, which demonstrated the reliability and advantages of this work.https://www.mdpi.com/1424-8220/17/9/2153remote sensing3D reconstructionsuper-generalized stereo-pairsartificial bee colony algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Yiming Yan
Nan Su
Chunhui Zhao
Liguo Wang
spellingShingle Yiming Yan
Nan Su
Chunhui Zhao
Liguo Wang
A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs
Sensors
remote sensing
3D reconstruction
super-generalized stereo-pairs
artificial bee colony algorithm
author_facet Yiming Yan
Nan Su
Chunhui Zhao
Liguo Wang
author_sort Yiming Yan
title A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs
title_short A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs
title_full A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs
title_fullStr A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs
title_full_unstemmed A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs
title_sort dynamic multi-projection-contour approximating framework for the 3d reconstruction of buildings by super-generalized optical stereo-pairs
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2017-09-01
description In this paper, a novel framework of the 3D reconstruction of buildings is proposed, focusing on remote sensing super-generalized stereo-pairs (SGSPs). As we all know, 3D reconstruction cannot be well performed using nonstandard stereo pairs, since reliable stereo matching could not be achieved when the image-pairs are collected at a great difference of views, and we always failed to obtain dense 3D points for regions of buildings, and cannot do further 3D shape reconstruction. We defined SGSPs as two or more optical images collected in less constrained views but covering the same buildings. It is even more difficult to reconstruct the 3D shape of a building by SGSPs using traditional frameworks. As a result, a dynamic multi-projection-contour approximating (DMPCA) framework was introduced for SGSP-based 3D reconstruction. The key idea is that we do an optimization to find a group of parameters of a simulated 3D model and use a binary feature-image that minimizes the total differences between projection-contours of the building in the SGSPs and that in the simulated 3D model. Then, the simulated 3D model, defined by the group of parameters, could approximate the actual 3D shape of the building. Certain parameterized 3D basic-unit-models of typical buildings were designed, and a simulated projection system was established to obtain a simulated projection-contour in different views. Moreover, the artificial bee colony algorithm was employed to solve the optimization. With SGSPs collected by the satellite and our unmanned aerial vehicle, the DMPCA framework was verified by a group of experiments, which demonstrated the reliability and advantages of this work.
topic remote sensing
3D reconstruction
super-generalized stereo-pairs
artificial bee colony algorithm
url https://www.mdpi.com/1424-8220/17/9/2153
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