• Title/Summary/Keyword: Building detection

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Building Change Detection Methodology in Urban Area from Single Satellite Image (단일위성영상 기반 도심지 건물변화탐지 방안)

  • Seunghee Kim;Taejung Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1097-1109
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    • 2023
  • Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

Vibration based damage detection in a scaled reinforced concrete building by FE model updating

  • Turker, Temel;Bayraktar, Alemdar
    • Computers and Concrete
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    • v.14 no.1
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    • pp.73-90
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    • 2014
  • The traditional destructive tests in damage detection require high cost, long consuming time, repairing of damaged members, etc. In addition to these, powerful equipments with advanced technology have motivated development of global vibration based damage detection methods. These methods base on observation of the changes in the structural dynamic properties and updating finite element models. The existence, location, severity and effect on the structural behavior of the damages can be identified by using these methods. The main idea in these methods is to minimize the differences between analytical and experimental natural frequencies. In this study, an application of damage detection using model updating method was presented on a one storey reinforced concrete (RC) building model. The model was designed to be 1/2 scale of a real building. The measurements on the model were performed by using ten uni-axial seismic accelerometers which were placed to the floor level. The presented damage identification procedure mainly consists of five steps: initial finite element modeling, testing of the undamaged model, finite element model calibration, testing of the damaged model, and damage detection with model updating. The elasticity modulus was selected as variable parameter for model calibration, while the inertia moment of section was selected for model updating. The first three modes were taken into consideration. The possible damaged members were estimated by considering the change ratio in the inertia moment. It was concluded that the finite element model calibration was required for structures to later evaluations such as damage, fatigue, etc. The presented model updating based procedure was very effective and useful for RC structures in the damage identification.

Building Detection Using Shadow Information in KOMPSAT Satellite Imagery (그림자 정보를 이용한 KOMPSAT 위성영상에서의 건물 검출)

  • 예철수;이쾌희
    • Korean Journal of Remote Sensing
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    • v.16 no.3
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    • pp.235-242
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    • 2000
  • This paper presents a method to detect buildings using shadow information in satellite imagery. We classify image into three categories of building region, shadow region and background region to find buildings with consistent intensity. After the removal of noises in building regions and shadow regions, buildings adjacent to shadow regions are detected using the constraint of building and shadow sizes. The algorithm has been applied to KOMPSAT and SPOT images and the result showed buildings are efficiently detected.

VIRTUAL CONSTRUCTION OF TRANSFER FLOORS IN REINFORCED CONCRETE BUILDING USING BIM

  • Kwangho So;Bohwan Oh;Yongjik Lee;Hyungeun Lee;Taehun Ha
    • International conference on construction engineering and project management
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    • 2011.02a
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    • pp.12-16
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    • 2011
  • Building Information Modeling (BIM) is being widely spread in AEC industry worldwide and also in South Korea. Although the creation of digital model is better to be started at design stage, it can also improve the productivity of construction by simulating the actual construction process and environment. This paper presents application of BIM-based simulations related with design changes to transfer floors in 58-storey reinforced concrete office building. Transfer floor is not only a structurally important part of the building but also a challenging part of the actual construction in terms of sequence and period due to the complexity of the work. Preconstruction of rebar, mechanical, and plumbing is performed to review the construction drawings and to perform clash detection. Each item of application is evaluated for its effectiveness on actual construction and for the development potential.

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A Study on Object Detection in Region-of-Interest Algorithm using Adjacent Frames based Image Correction Algorithm for Interactive Building Signage

  • Lee, Jonghyeok;Choi, Jinyeong;Cha, Jaesang
    • International Journal of Internet, Broadcasting and Communication
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    • v.10 no.2
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    • pp.74-78
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    • 2018
  • Recently, due to decrease hardware prices and the development of technology, analog signage has been changing to digital signage for providing content such as advertisements, videos. Furthermore, in order to provide advertisements and contents to users more effectively, technical researches are being conducted in various industries. In addition, including digital signage that uses displays, it can be seen that it provides advertisements and contents using diverse devices such as LED signage, smart pads, and smart phones. However, most digital signage is installed in one place to provide contents and provides interactivity through simple events such as manual content provision or touch. So, in this paper, we suggest a new object detection algorithm based on an adjacent frames based image correction algorithm for interactive building signage.

A Strategy to Improve Customer Service for Apartment Building Units (GIS를 기반으로한 실시간 실내공간관리 시스템 개발 - COEX Test Bed -)

  • Na, Kido;Lee, Gwang-Gook;Kim, Whoi-Yul;Kim, Jea-Jun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2009.11a
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    • pp.269-272
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    • 2009
  • The environment of Ubiquitous in terms of improvement is being expanded to various fields and time enabled system. Thus, a real-time spatial information management system has been developed by integrating a human movement detection system into a SICS(Spatial Information Control System) engine that can integrally manage inside spatial information extracted from 3D CAD and outside spatial information of GIS. The add-on program was developed to extract spatial information necessary for the SICS engine from 3D CAD information, and a human movement detection system was developed. Test bed was operated for 2weeks and indoor human flow information was found out by zone. Also, the direction of future research was decided through a test bed.

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Performance Evaluation of a BACnet-based Fire Detection and Monitoring System for use in Buildings

  • Song Won-Seok;Hong Seung-Ho
    • International Journal of Control, Automation, and Systems
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    • v.4 no.1
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    • pp.70-76
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    • 2006
  • The objective of this paper is to propose a reference model of a fire detection and monitoring system using MS/TP protocol. The reference model is designed to satisfy the requirements of response time and flexibility. The reference model is operated on the basis of BACnet, a standard communication protocol for building automation systems. Validity of the reference model was examined using a simulation model. This study also evaluated the performance of the BACnet-based fire detection and monitoring system in terms of network-induced delay. Simulation results show that the reference model satisfies the requirements of the fire detection and monitoring system.

X-Ray Security Checkpoint System Using Storage Media Detection Method Based on Deep Learning for Information Security

  • Lee, Han-Sung;Kim Kang-San;Kim, Won-Chan;Woo, Tea-Kun;Jung, Se-Hoon
    • Journal of Korea Multimedia Society
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    • v.25 no.10
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    • pp.1433-1447
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    • 2022
  • Recently, as the demand for physical security technology to prevent leakage of technical and business information of companies and public institutions increases, the high tech companies are operating X-ray security checkpoints at building entrances to protect their intellectual property and technology. X-ray security checkpoints are operated to detect cameras and storage media that may store or leak important technologies in the bags of people entering and leaving the building. In this study, we propose an X-ray security checkpoint system that automatically detects a storage medium in an X-ray image using a deep learning based object detection method. The proposed system consists of an edge computing unit and a cloud-computing unit. We employ the RetinaNet for automatic storage media detection in the X-ray security checkpoint images. The proposed approach achieved mAP of 95.92% on private dataset.

Pretreatment and Rapid Detection Methods for Wastewater-Based Epidemiology (하수역학 구축을 위한 시료 전처리 기술과 신속검출기술)

  • Lee Jai-Yeop;Lee Bokjin;Jesmin Akter;Ahn Chang Hyuk;Kim Ilho
    • Journal of Korean Society on Water Environment
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    • v.39 no.1
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    • pp.102-110
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    • 2023
  • Wastewater Based Epidemiology (WBE) provides useful information not only on the use of illegal drugs in the community, but also on the presence of hygiene and health products and infectious pathogens in sewage facilities. As a consequence of the SARS-CoV-19 virus epidemic in 2019, monitoring the status of the infection is of utmost importance. SARS-CoV-19 was also detected in sewage, and the number and trend of infections in the community suggest that the application of the WBE system would be useful and appropriate. This study introduces a pre-treatment concentration method including viruses in sewage samples. A total of seven methods which were subdivided into methods for adsorption-extraction, ultra-filtration, PEG precipitation, and ultra-centrifugation, and the results for analyzing the recovery rates were included. Meanwhile, it is necessary to pay attention to rapid detection technologies which analyze infectious pathogens at the site of sewage facilities. These can include ELISA, FTIR, SERS, and biosensor based on the detection principle, and the characteristics, advantages, and disadvantages of each were summarized herein. If rapid detection technologies and accurate quantitative analyses are further developed, the use of sewage mechanics in response to pandemic viruses is expected to expand further.

Analysis of Building Object Detection Based on the YOLO Neural Network Using UAV Images (YOLO 신경망 기반의 UAV 영상을 이용한 건물 객체 탐지 분석)

  • Kim, June Seok;Hong, Il Young
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.381-392
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    • 2021
  • In this study, we perform deep learning-based object detection analysis on eight types of buildings defined by the digital map topography standard code, leveraging images taken with UAV (Unmanned Aerial Vehicle). Image labeling was done for 509 images taken by UAVs and the YOLO (You Only Look Once) v5 model was applied to proceed with learning and inference. For experiments and analysis, data were analyzed by applying an open source-based analysis platform and algorithm, and as a result of the analysis, building objects were detected with a prediction probability of 88% to 98%. In addition, the learning method and model construction method necessary for the high accuracy of building object detection in the process of constructing and repetitive learning of training data were analyzed, and a method of applying the learned model to other images was sought. Through this study, a model in which high-efficiency deep neural networks and spatial information data are fused will be proposed, and the fusion of spatial information data and deep learning technology will provide a lot of help in improving the efficiency, analysis and prediction of spatial information data construction in the future.