• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.68-73
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• 2008

Recently, construction management technology based on information technology is being changed from numerical information management to visual information management with virtual reality (VR) method. This study suggests a IDEF0 model for development process of VR system for the planning, design and construction phases of civil engineering project. And the simulation functions by each phase based on VR were developed by using the suggested IDEF0 model. The developed virtual construction system can be used as an effective design review tool by visualization of design information based on 3D object.

• Smart Media Journal
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• v.12 no.9
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• pp.134-141
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• 2023

In this paper, we propose a ToF-Stereo fusion sensor system for 3D space scanning that increases the recognition rate of 3D objects, guarantees object detection quality, and is robust to the environment. The ToF-Stereo sensor fusion system uses a method of fusing the sensing values of the ToF sensor and the Stereo RGB sensor, and even if one sensor does not operate, the other sensor can be used to continuously detect an object. Since the quality of the ToF sensor and the Stereo RGB sensor varies depending on the sensing distance, sensing resolution, light reflectivity, and illuminance, a module that can adjust the function of the sensor based on reliability estimation is placed. The ToF-Stereo sensor fusion system combines the sensing values of the ToF sensor and the Stereo RGB sensor, estimates the reliability, and adjusts the function of the sensor according to the reliability to fuse the two sensing values, thereby improving the quality of the 3D space scan.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.263-269
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• 2012

Grouping of characters in a 3D game can be very effective to play. An 3D game characters grouping method is proposed using Object Feature vector depending on their characteristics. In the case of NMT, the constitution of pattern is regular and directive. But MT is not. Such characteristic is extracted using Gabor Filter, then character is grouped. Through experiment, we obtain accuracy of more than 80% for grouping method using each feature. Thus, using this property, characters could be grouped effectively and it draws the game more speed and strategic actions as a result.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.47-54
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• 2009

Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.305-315
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• 2010

This research aims to develop a method to determine the 3D coordinates of an object point from overlapping omni-directional images acquired by a ground mobile mapping system and assess their accuracies. In the proposed method, we first define an individual coordinate system on each sensor and the object space and determine the geometric relationships between the systems. Based on these systems and their relationships, we derive a straight line of the corresponding object point candidates for a point of an omni-directional image, and determine the 3D coordinates of the object point by intersecting a pair of straight lines derived from a pair of matched points. We have compared the object coordinates determined through the proposed method with those measured by GPS and a total station for the accuracy assessment and analysis. According to the experimental results, with the appropriate length of baseline and mutual positions between cameras and objects, we can determine the relative coordinates of the object point with the accuracy of several centimeters. The accuracy of the absolute coordinates is ranged from several centimeters to 1 m due to systematic errors. In the future, we plan to improve the accuracy of absolute coordinates by determining more precisely the relationship between the camera and GPS/INS coordinates and performing the calibration of the omni-directional camera

• Land and Housing Review
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• v.14 no.3
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• pp.145-155
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• 2023

Recently, with the widespread adoption of Building Information Modeling (BIM) technology in the construction industry, various object detection algorithms have been used to verify errors between 3D models and actual construction elements. Since the characteristics of objects vary depending on the type of construction facility, such as buildings, bridges, and tunnels, appropriate methods for object detection technology need to be employed. Additionally, for object detection, initial object images are required, and to obtain these, various methods, such as drones and smartphones, can be used for image acquisition. The study uses a 360° camera optimized for internal tunnel imaging to capture initial images of the tunnel structures of railway and road facilities. Various object detection methodologies including the YOLO, SSD, and R-CNN algorithms are applied to detect actual objects from the captured images. And the Faster R-CNN algorithm had a higher recognition rate and mAP value than the SSD and YOLO v5 algorithms, and the difference between the minimum and maximum values of the recognition rates was small, showing equal detection ability. Considering the increasing adoption of BIM in current railway and road construction projects, this research highlights the potential utilization of 360° cameras and object detection methodologies for tunnel facility sections, aiming to expand their application in maintenance.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.977-982
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• 2007

There have been many efforts in automatic object recognition using computing technologies. Especially in the development of automated construction equipment, automatic object recognition is very important issue for the proper equipment maneuvering. 3D laser scanning, which uses (time-of-flight) method to construct the 3-dimensional information, is applied to the civil earth work environment for its high accuracy, quick data collection, and object recognition capability that will be developed by the authors in the future. The 3D earth model is also used as a fundamental information for intelligent earth work task planning. This paper presents the analysis of the 3D laser scanner market and selection of the most optimum 3D scanner for the intelligent earth work planning. As well as the hardware configuration for the automated 3D earth modeling is developed but also the software structure and detailed user interface are designed in this research. In addition, it is presented in this paper that the accuracy comparison test between TotalStation(R) which is a traditional survey tool and ScanStation(R). The accuracy test is done by relative distance measurement using known targets.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.330-337
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• 2022

Research on object detection algorithms using 2D data has already progressed to the level of commercialization and is being applied to various manufacturing industries. Object detection technology using 2D data has an effective advantage, there are technical limitations to accurate data generation and analysis. Since 2D data is two-axis data without a sense of depth, ambiguity arises when approached from a practical point of view. Advanced countries such as the United States are leading 3D data collection and research using 3D laser scanners. Existing processing and detection algorithms such as ICP and RANSAC show high accuracy, but are used as a processing speed problem in the processing of large-scale point cloud data. In this study, PointNet a representative technique for detecting objects using widely used 3D point cloud data is analyzed and described. And RandLA-Net, which overcomes the limitations of PointNet's performance and object prediction accuracy, is described a review of detection technology using point cloud data was conducted.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.651-655
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• 2003

본 논문에서는 맞춤 가구 제작 및 제작된 가구의 배치를 위한 효율적이면서도 사용하기 용이한 3D Visual 디스플레이 시스템을 개발하고자 한다. AutoCAD로 만들어진 평면파일(*.dxf) 그리고 3D 제작툴로 만들어진 오브젝트 파일(*.3ds)을 이용하여 현실감 있도록 시뮬레이션 하는 것을 목표로 한다. 2D로 제작된 AutoCAD 평면 설계 파일을 이용하여 평면 파일을 3D 투시도로 변환하고 3DS파일로 구축한 객체들을 배치한 뒤 텍스처매핑, 렌더링 등을 구현하여 최대한 현실감을 낼 수 있도록 개발한다.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.11-17
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• 2012

The study aims to secure an integrated UFID system-based ID system as it defines the three-dimensional land registration record through selection and standardization of objects. By comparing the integrated ID system secured by the study and the objected ID system proposed by Seoul City, the study came up with practicality of the integrated ID system for the three-dimensional land registration record information system. An integrated UFID-based intellectual spacial information which is consisted of 41 figures in total was developed by the study. The study confirmed the practicality of the integrated ID system by comparing it with the objected ID of the three dimensional land registration record information system established by Seoul City.