• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.509-516
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• 2022

Accurate pose prediction of objects in 3D space is an important visual recognition technique widely used in many applications such as scene understanding in both indoor and outdoor environments, robotic object manipulation, autonomous driving, and augmented reality. Most previous works for object pose estimation have the limitation that they require an exact 3D CAD model for each object. Unlike such previous works, this paper proposes a novel neural network model that can predict the poses of unknown objects based on only their RGB color images without the corresponding 3D CAD models. The proposed model can obtain depth maps required for unknown object pose prediction by using an adaptive depth estimator, AdaBins,. In this paper, we evaluate the usefulness and the performance of the proposed model through experiments using benchmark datasets.

• Spatial Information Research
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• v.21 no.4
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• pp.83-89
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• 2013

Recently various contents have been produced using the techniques that require high-performance computing process. A lot of services have been being producted as AR(Augmented Reality) service being combined with mobile information service that a moving user search various information based on one's location with. Mobile information service has a characteristic that it needs to get new information according to the location an user moves to. The characteristic requires a lot of communications when user search information moving to a different location. In order to make up for this drawback, we propose a prefetching technique based on speed and viewing angle in this paper. Existing prefetching techniques retrieve the following location of users considering moving speed and direction of the users. The data showed on the screen in AR is limited by the viewing angle of the mobile device. Due to the problems we discussed above, existing prefetching techniques have a demerit that they retrieve a lot more data than needed actually. We propose more efficient way of retrieving data with AR using the viewing angle of the mobile device. The method we propose reduces retrieval of unnecessary location using the users' speed, direction and viewing angle. This method is more efficient than the existing ways of retrieval because we don't need as many data.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.225-231
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• 2022

Transcendence of space and time, virtual reality, augmented reality, etc. are being realized through the latest technologies in the era of the 4th industrial revolution. In a situation where they are currently experiencing artificial intelligence, augmented reality, big data, etc., the degree of interest in the latest technologies of the 4th industrial revolution for radiology students, the necessary competencies in the 4th industrial revolution era, and the prospect of the radiation field employment environment in the 4th industrial revolution era The purpose of this study was to find out the level of awareness of From February 7th to February 18th, 2022, surveys on awareness were analyzed using questionnaires for 2nd and 3rd year students in the Department of Radiology at S University in Daegu. As a result of the study, the level of interest in 3D modeling was shown to be the highest with an average of 3.34 ± 1.09 points, and interest in big data and artificial intelligence was also shown with an average of 3.27 ± 1.17 and 3.33 ± 1.07 points. In addition, the correlation between the awareness of the necessary competencies in the 4th industrial revolution era and the awareness of the prospects for employment in the radiation field in the 4th industrial revolution era was the highest (r=0.778, p<0.01), and the interest in the latest technologies in the 4th industrial revolution and the 4th industrial revolution It was found that there was also a correlation between the perceptions of the necessary capabilities of the times (r=0.694, p<0.01). In the era of the 4th industrial revolution, it is judged that it is necessary to strengthen professional education that can handle the latest technologies such as 3D printing, artificial intelligence, and big data, and to strengthen employment capabilities related to the latest technologies in the field of radiation medical technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.287-293
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• 2018

The Korean peninsula has been known as an area that is free of volcanic disasters. However, recent observations and research results of volcanoes in Far East Asia, including Baedu Mountain and Japanese volcanoes, show that the Korean peninsula is no longer a safe area from volcanic disasters. Since 2012, the Korean government has been developing an IT-based construction technology, VDRS (Volcanic Disaster Response System), for effective volcanic disaster response system. The main users of VDRS are public officers in central or local governments. However, most of them have little experience and knowledge about volcanic disasters. Therefore, it is essential to develop education contents and implement training on volcanic disaster response for effective response in a real disaster situation. In this paper, we deal with the development of a mobile application based on virtual reality (VR) for realistic volcanic disaster response training. The objectives of training are the delivery of knowledge and experience for volcanic disasters. First, VR contents were generated based on spatial information. A 3D model was constructed based on a Digital Elevation Model (DEM), and visualization models for meterological effects and various volcanic disaster diffusion effects were implemented for the VR contents. Second, the mobile application for the volcanic disaster response training was implemented. A 12-step story board is proposed for volcanic disaster experience. The application was developed with the Unity3D engine based on the proposed story board to deliver knowledge of various volcanic disasters (volcanic ash, pyroclastic flows, volcanic mudflow etc.). The results of this paper will be used for volcanic disaster response and prevention training and for more realistic training linked with augmented reality technology in the future.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.29-63
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• 2014

This study attempted to reveal the characteristics of the Y generation, to derive the services of the next generation digital library, and to compare differences between the demands of the baby boom generation and the Y generation to some extent. As a result, first, it is shown that the digital device the Y generation uses the most, was a cell phone or smartphone, followed by desktop PC, notebook PC, and digital camera. Although there were some differences, the Y generation's use ratio of digital devices was substantially similar to the baby boomers'. Second, there was a significant difference between the Y generation and baby boom generation in terms of using digital services. While the Y generation used internet portals the most, the baby boom generation used e-mail service the most. Third, we surveyed the services which the Y generation and baby boom generation require for the next generation digital libraries, by grouping as follows: the cloud service, infinite creative space (maker space), big data, augmented reality, Google Glass, context-aware technologies, semantic services, SNS service, digital textbook service, RFID and QRCode service, library space configuration, a state-of-the-art display technology, and other innovative services. While the most demanded service by the Y generation was big data service, the baby boom generation most demanded digital textbook service.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.137-152
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• 2017

The decline in the price of IT devices and the development of the Internet have created a new field called Internet of Things (IoT). IoT, which creates new services by connecting all the objects that are in everyday life to the Internet, is pioneering new forms of business that have not been seen before in combination with Big Data. The prospect of IoT can be said to be unlimited in its utilization. In addition, studies of standardization organizations for smooth connection of these IoT devices are also active. However, there is a part of this study that we overlook. In order to control IoT equipment or acquire information, it is necessary to separately develop interworking issues (IP address, Wi-Fi, Bluetooth, NFC, etc.) and related application software or apps. In order to solve these problems, existing research methods have been conducted on augmented reality using GPS or markers. However, there is a disadvantage in that a separate marker is required and the marker is recognized only in the vicinity. In addition, in the case of a study using a GPS address using a 2D-based camera, it was difficult to implement an active interface because the distance to the target device could not be recognized. In this study, we use 3D Depth recognition camera to be installed on smartphone and calculate the space coordinates automatically by linking the distance measurement and the sensor information of the mobile phone without a separate marker. Coordination inquiry finds equipment of IoT and enables information acquisition and control of corresponding IoT equipment. Therefore, from the user's point of view, it is possible to reduce the burden on the problem of interworking of the IoT equipment and the installation of the app. Furthermore, if this technology is used in the field of public services and smart glasses, it will reduce duplication of investment in software development and increase in public services.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.59-75
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• 2019

This study was carried out to explore the 4th Industrial Revolution technology from the perspective of the landscape industry to provide the basic data necessary to increase the virtuous circle value. The 4th Industrial Revolution, the characteristics of the landscape industry and urban regeneration were considered and the methodology was established and studied including the technical classification system suitable for systematic research, which was selected as a framework. First, the 4th Industrial Revolution technology based on digital data was selected, which could be utilized to increase the value of the virtuous circle for the landscape industry. From 'Element Technology Level', and 'Core Technology' such as the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Robot, 'Peripheral Technology', Virtual or Augmented Reality, Drones, 3D 4D Printing, and 3D Scanning were highlighted as the 4th Industrial Revolution technology. It has been shown that it is possible to increase the value of the virtuous circle when applied at the 'Trend Level', in particular to the landscape industry. The 'System Level' was analyzed as a general-purpose technology, and based on the platform, the level of element technology(computers, and smart devices) was systematically interconnected, and illuminated with the 4th Industrial Revolution technology based on digital data. The application of the 'Trend Level' specific to the landscape industry has been shown to be an effective technology for increasing the virtuous circle values. It is possible to realize all synergistic effects and implementation of the proposed method at the trend level applying the element technology level. Smart gardens, smart parks, etc. have been analyzed to the level they should pursue. It was judged that Smart City, Smart Home, Smart Farm, and Precision Agriculture, Smart Tourism, and Smart Health Care could be highly linked through the collaboration among technologies in adjacent areas at the Trend Level. Additionally, various utilization measures of related technology applied at the Trend Level were highlighted in the process of urban regeneration, public service space creation, maintenance, and public service. In other words, with the realization of ubiquitous computing, Hyper-Connectivity, Hyper-Reality, Hyper-Intelligence, and Hyper-Convergence were proposed, reflecting the basic characteristics of digital technology in the landscape industry can be achieved. It was analyzed that the landscaping industry was effectively accommodating and coordinating with the needs of new characters, education and consulting, as well as existing tasks, even when participating in urban regeneration projects. In particular, it has been shown that the overall landscapig area is effective in increasing the virtuous circle value when it systems the related technology at the trend level by linking maintenance with strategic bridgehead. This is because the industrial structure is effective in distributing data and information produced from various channels. Subsequent research, such as demonstrating the fusion of the 4th Industrial Revolution technology based on the use of digital data in creation, maintenance, and service of actual landscape space is necessary.

• Journal of the Korean Geographical Society
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• v.30 no.2
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• pp.132-145
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• 1995

The Purpose of this study is to integrate two opposite paradigms, (development from above) and (development from below), by means of A. Giddenss (structuration theory) and to provide practical development strategies on the basis of integrated paradigm. The integration of these two opposite paradigms is in fact the internalization of epistemological overcoming of 'dependency', which means the structural transformation of dualistic thinking into monistic thinking that the enlargement of capitalist world-system can be 'development' and it may also be 'dependency'. Therefore the practical main issue of this integrated paradigm results in how peripheral countries should achieve self-reliant and continuous development under the circumstances of dependency. To achieve such development while resisting the growing arrogance of transnational capital, development strategies should be prepared to maker revitalized political community designed to fit a human scale and for the economy to be subordinated to the political will of the community. And at the same time the 'empowerment' of people should be strengthened.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.211-221
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• 2012

To utilize omni-directional images acquired by a rotating line camera for indoor spatial information services, we should register precisely the images with respect to an indoor coordinate system. In this study, we thus develop a georeferencing method to estimate the exterior orientation parameters of an omni-directional image - the position and attitude of the camera at the acquisition time. First, we derive the collinearity equations for the omni-directional image by geometrically modeling the rotating line camera. We then estimate the exterior orientation parameters using the collinearity equations with indoor control points. The experimental results from the application to real data indicate that the exterior orientation parameters is estimated with the precision of 1.4 mm and $0.05^{\circ}$ for the position and attitude, respectively. The residuals are within 3 and 10 pixels in horizontal and vertical directions, respectively. Particularly, the residuals in the vertical direction retain systematic errors mainly due to the lens distortion, which should be eliminated through a camera calibration process. Using omni-directional images georeferenced precisely with the proposed method, we can generate high resolution indoor 3D models and sophisticated augmented reality services based on the models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.63-70
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• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.