• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.136-150
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• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.121-130
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• 2011

This paper highlights the reconstruction of the rectilinear type of 3D rooftop model from satellite image data using centroid neural network. The main idea of the proposed 3D reconstruction method is based on the grouping of 3D line segments. 3D lines are extracted by 2D lines and DEM (Digital Elevation Map) data evaluated from a pair of stereo images. Our grouping process consists of two steps. We carry out the first grouping process to group fragmented or duplicated 3D lines into the principal 3D lines, which can be used to construct the rooftop model, and construct the groups of lines that are parallel each other in the second step. From the grouping result, 3D rooftop models are reconstructed by the final clustering process. High-resolution IKONOS images are utilized for the experiments. The experimental result's indicate that the reconstructed building models almost reflect the actual position and shape of buildings in a precise manner, and that the proposed approach can be efficiently applied to building reconstruction problem from high-resolution satellite images of an urban area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.737-742
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• 2017

Recently, unconventional high-rise building shapes have attracted attention as a landmark of metropolitan cities and the search for innovative building forms in architecture is ongoing. In this study, $Isotruss^{(R)}$ grid(ITG) used in smaller scale structures was applied to building structural systems and its structural performance was examined. The structural behavior of an ITG was compared with that of a diagrid structure as a reference structure. The stiffness-based design method of the diagrid system was used for the preliminary design stage of member sizing in an ITG. The structural design of 16, 32, and 48-story buildings was carried out for the two systems with the same size. The angle of the inclined columns for ITG and diagrid was $59^{\circ}$ and $68.2^{\circ}$, respectively. The lateral stiffness, steel tonnage of the exterior frame, axial strength ratio, story drift ratio, and natural frequency of the two systems were compared. Based on the analysis result of 6 buildings, the two systems had similar structural capacity; 93.3% and 88.7% of the lateral load was carried by the perimeter frame in the ITG system and diagrid system, respectively. This suggests that the ITG system is better in arranging core columns. Therefore, the proposed ITG system has not only a unique façade, but also substantial structural capacity equivalent to the existing system.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.33-38
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• 2005

The goal of this study is to segment building points effectively utilizing scan-line characteristics of airborne laser scanner. Points are classified as to their altitude similarity and adjacency with other classified points, and point searching range for the classification is restricted within some number of scan-lines, preventing classification speed from lowering as the process goes on. Besides, we detected wrong discrimination of one object into more than two classes, then integrated them into a single class. Consequently we could discriminate points of each building from others, its annexes and none building points simultaneously.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1110-1112
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• 2015

에너지 절감을 위해 다양한 분야에서 노력을 기울이고 있지만 전체 에너지 사용량의 약 20% 이상을 차지하는 건물 분야는 정부의 정책과 제도적인 지원 하에 에너지 절감활동을 활발하게 진행하고 있다. 특히 $3000m^2$ 이상의 중대형 건물의 경우 BEMS(Building Energy Management System)기반의 건물에너지 관리가 의무화 될 예정이다. 하지만 기존 BEMS의 경우 특정 기업에 의한 단독 솔루션 형태로 제공되고 있어 BEMS간 데이터 상호호환성을 보장하지 않고, 단순 모니터링 기능에 의존하여 저장/관리 되지 않고 버려지는 데이터들이 많아 차후 문제가 발생한 경우 과거 데이터를 통한 분석 작업에 어려움이 있다. 따라서 본 논문에서는 건물에너지 통합관리 측면에서 원격지에 설치된 다양한 BEMS들의 센서/미터 데이터들을 웹을 통해 수집하고 데이터 웨어하우스에 저장/관리되며 건물에너지 통계, 분석 및 진단을 가능하도록 하는 데이터 웨어하우스 기반의 원격 건물에너지 통합 관리 시스템 설계에 대해 서술한다.

• Journal of Korean Association for Spatial Structures
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• v.11 no.4
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• pp.89-99
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• 2011

As the scope of the target of terrorism is recently extending, the danger of domestic terroristic attacks is increasing constantly, and the form of terrorism is changing from hard targets such as significant facilities of the country into soft target of multi-complex buildings such as skyscrapers. Accordingly this study analyzes the terrorism threat level on skyscrapers by comparing the assessment results of the terrorism threat level on skyscrapers and high-rise buildings with the assessment results of the terrorism threat level on low-rise buildings through fema 455 - Rapid Visual Screening. As a result, skyscrapers and high-rise buildings are relatively higher threat rating than consequences and vulnerability rating. This is caused by the fact that the terrorism threat level on skyscrapers is high due to their residents and their national or regional symbolism and visibility

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.11-15
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• 1999

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.341-348
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• 2020

The ability to extract useful information from an image, such as the human eye, is an interface technology essential for AI computer implementation. The building recognition technology has a lower recognition rate than other image recognition technologies due to the various building shapes, the ambient noise images according to the season, and the distortion by angle and distance. The computer vision based building recognition algorithms presented so far has limitations in discernment and expandability due to manual definition of building characteristics. This paper introduces the deep learning CNN (Convolutional Neural Network) model, and proposes new method to improve the recognition rate even by changes of building images caused by season, illumination, angle and perspective. This paper introduces the partial images that characterize the building, such as windows or wall images, and executes the training with whole building images. Experimental results show that the building recognition rate is improved by about 14% compared to the general CNN model.

• Journal of the Korea Organic Resources Recycling Association
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• v.26 no.1
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• pp.13-19
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• 2018

25 local districts in Seoul have been running Waste Transfer Stations(WTSs) to secure regional collection bases, to connect between collection systems and waste treatment systems, and to commit various pre-screening of mixed wastes. There were, however, few previous researches to define how much WTSs are beneficial to waste collection system at least in Korea. So this study analyzed costs of waste collection systems with varied haul distances from waste sources(WSs) to WTS or building types of WTSs. Major results showed that the closer WTS is to WS or the cheaper the construction cost of WTS is, the lower the cost of waste collection system is. There was an additional result that WTS system with more than 15 km of total haul distance might be useful in Seoul and encapsulation of WTS in building or underground will make effective total haul distances longer up to 35km.

• Journal of IKEEE
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• v.16 no.2
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• pp.95-101
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• 2012

A novel approach for the reconstruction of 3D building model from aerial image data is proposed in this paper. In this approach, a Centroid Neural Network (CNN) with a metric of line segments is proposed for connecting low-level linear structures. After the straight lines are extracted from an edge image using the CNN, rectangular boundaries are then found by using an edge-based grouping approach. In order to avoid producing unrealistic building models from grouping lined segments, a hierarchical grouping method is proposed in this paper. The proposed hierarchical grouping method is evaluated with a set of aerial image data in the experiment. The results show that the proposed method can be successfully applied for the reconstruction of 3D building model from satellite images.