• Korean Journal of Geomatics
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• v.4 no.2
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• pp.39-45
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• 2004

Building reconstruction attempts to generate geometric and radiometric models of existing buildings usually from sensory data, which have been traditionally aerial or satellite images, more recently airborne LIDAR data, or the combination of these data. Extensive studies on building reconstruction from these data have developed some competitive algorithms with reasonable performance and some degree of automation. Nevertheless, the level of details and completeness of the reconstructed building models often cannot reach the high standards that is now or will be required by various applications in future. Hence, the use of terrestrial sensory data that can provide higher resolution and more complete coverage has been intensively emphasized. We developed a fusion framework for building reconstruction from terrestrial sensory data, that is, points from a laser scanner, images from digital camera, and absolute coordinates from a total station. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large complex existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS with reasonable resources.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.83-86
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• 2005

This paper presents a method for point-based 3D building reconstruction using LiDAR data and digital map. The proposed method consists of three processes: extraction of building roof points, identification of roof types, and 3D building reconstruction. After extracting points inside the polygon of building, the ground surface, wall and tree points among the extracted points are removed through the filtering process. The filtered points are then fitted into the flat plane using ODR(Orthogonal Distance Regression). If the fitting error is within the predefined threshold, the surface is classified as a flat roof. Otherwise, the surface is fitted and classified into a gable or arch roof through RMSE analysis. Based on the roof types identified in automated fashion, the 3D building reconstruction is performed. Experimental results showed that the proposed method classified successfully three different types of roof and that the fusion of LiDAR data and digital map could be a feasible method of modelling 3D building reconstruction.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.47-48
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• 2022

In Korea, construction and development has been continued rapidly since the 1970s, and the reconstruction and renovation market has recently been activated to improve old buildings. Most of the environmental evaluation of reconstruction and renovation projects is focused on the use of operating energy, and It is necessary to analyze carbon emissions throughout the life cycle for a comprehensive evaluation of reconstruction and remodeling projects. Therefore, this study quantitatively predicted carbon emissions from reconstruction and renovation based on ISO 14040s through case analysis for the purpose of evaluating the carbon emissions of renovated buildings from the perspective of the whole life cycle. In additional, the amount of carbon savings of each was analyzed through comparison with existing building.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.529-534
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• 2004

The increasing need and use of 3D GIS particularly in urban areas has produced growing attention on building reconstruction. Nowadays, the use of close-range data for building reconstruction has been intensively emphasized since they can provide higher resolution and more complete coverage than airborne sensory data. We developed a fusion approach for building reconstruction from both points and images. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.78-82
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• 2007

This paper propose a building reconstruction method of urban area for a 3D GIS with stereo images. The 3D reconstruction is performed by the grouping 3D line segments extracted from the stereo matching of salient edges which are derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.

• Journal of Electrical Engineering and Technology
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• v.3 no.3
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• pp.436-443
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• 2008

This paper presents a new method for building detection and reconstruction from aerial images. In our approach, we extract useful building location information from the generated disparity map to segment the interested objects and consequently reduce unnecessary line segments extracted in the low level feature extraction step. Hypothesis selection is carried out by using an undirected graph, in which close cycles represent complete rooftops hypotheses. We test the proposed method with the synthetic images generated from Avenches dataset of Ascona aerial images. The experiment result shows that the extracted 3D line segments of the reconstructed buildings have an average error of 1.69m and our method can be efficiently used for the task of building detection and reconstruction from aerial images.

• Journal of IKEEE
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• v.12 no.1
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• pp.51-58
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• 2008

This paper presents a new method for building detection and reconstruction from aerial images. In our approach, we extract the useful building location information from the generated disparity map to obtain the segmentation of interested objects and thus reduce significantly unnecessary line segment extracted in low level feature extraction step. Hypothesis selection is carried out by using undirected graph in which close cycles represent complete rooftops hypotheses, and hypothesis are finally tested to contruct building model. We test the proposed method with synthetic images generated from Avenches dataset of Ascona aerial images. The experiment result shows that the extracted 3D line segments of the buildings can be efficiently used for the task of building detection and reconstruction from aerial images.

• Journal of the Korean housing association
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• v.21 no.6
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• pp.71-80
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• 2010

The purpose of this study is to classify defects of the residential building by analyzing the defect specified by prequalification of residential building reconstruction and to suggest the solution of the problem which can be arisen during each stage of plan, construction and maintenance. By sorting the main defects which is specified by pre-qualification of residential building reconstruction for three years from August 2006 to August 2009 into 4 catagories and analyzing the cause of the defects, we draw the way of maintenance to prevent the defects and make pleasant residential environment. The reason for the frequent defects from residential building is mainly deterioration. It occured on the finishing more than on the structure, which means that residents can find defects easier on the finishing than the structure and clear the demand for repair. The result of analyzing of pre-qualification of residential building reconstruction is that the defects mostly caused small, masonry constructed and lower apartment. The apartment which is not into legal right for maintenance naturally have more defects than the others. In conclusion, it is necessary to establish a law of obligation duty of the maintenance of small apartment.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.59-64
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• 2002

This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.470-473
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• 2005

This paper proposes a reconstruction method for the shape and color information of 3-dimensional buildings. The proposed method is range scanning by laser range finder and image coordinates' color information mapping to laser coordinate by a fixed CCD camera on laser range finder. And we make a 'Far-View' using high-resolution satellite image. The 'Far-View' is created that the height of building using DEM after contours of building extraction. The user select a region of 'Far View' and then, appear detailed 3D-reconstruction of building The outcomes apply to city plan, 3D-environment game and movie background etc.