• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• Spatial Information Research
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• v.23 no.5
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• pp.9-19
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• 2015

The popularity of smart devices and Location Based Services (LBSes) is increasing in part due to users demand for personalized information associated with their location. These services provide intuitive and realistic information by adopting Augmented Reality (AR) technology. This technology utilizes various sensors embedded in the mobile devices. However, these services have inherent problems due to the devices small screen size and the complexity of the real world environment; overlapping content on a small screen and placing icons without considering the user's possible movement. In order to solve these problems, this paper proposes a Mobile Augmented Reality Model with the application of Street Data. The model consists of two layers: "Real Space" and "Information Space". In the model, a user creates a query by scanning the nearby street with a camera in real space and searches accessible content along the street through the use of the information space. Furthermore, the results are placed on both sides of the street to solve the issue of Overlapping. Also, the proposed model is implemented for region "Aenigol", and the efficiency and usefulness of the model are verified.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.199-205
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• 2017

In this study, the design analysis and the explosion welding were made into a clad sheet by the convergence method in order to solve the problem of heat transfer to the guide due to the heating of the 3D printer heating block. The shear strength of the clad plate material was tested and the results were analyzed by thermal analysis, thermal conductivity and thermal imaging. The following conclusions were obtained. 3D modeling of the heating block made of copper and titanium clad plate material The thermal analysis showed that the surface temperature of the filament guide area was lower than the heating block surface temperature. The average shear strength of copper and titanium clad plate material was measured and the average value of 195.6MPa was obtained. The thermal conductivity of the heating block made of copper and titanium clad plate material was measured three times and the average value was $62.52W/m{\cdot}K$. The surface temperature of the heating block made of copper and titanium clad plate material was measured by a thermal imaging camera at a maximum of $107.3^{\circ}C$ and $183.2^{\circ}C$ at the filament guide. The temperature distribution was $89^{\circ}C$ lower than that of the existing filament.

• Korean Institute of Interior Design Journal
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• v.26 no.1
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• pp.33-42
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• 2017

Interior design especially the design developments for commercial spaces should ensure the economy of spaces. This is the marketing for space. It is necessary to understand the design elements of commercial space for the efficient using of digital media of space marketing. In this research decided to design application schemes for shopping mall by searching fashion shopping behaviors of users with persona-base scenario approach. Collected the information of users behavior base on case analysis of advance research to make personas. And develop scenario base personas for knowing the needs of users. And then made 4 schemes as the solution. Scheme 1. Customers can get the information and communication with the staff through with media screen in one room of shopping mall. The data of customers can be recorded for providing information or product recommendation personality. Forecast to preferred by group trip or customers that don't like walking around in shopping mall. Scheme 2. Install a media screen at entrance of a store in shopping mall and show special effect to raise customers' attention who walk through from the front of the store. Through with this customers will stay for long time and raise curiosity to get in the store. And the media screen also provide information of store and products. Scheme 3. Customers can get the information of products with using smart phone to scan QR cord in labels of products and record. Customers can finish whole shopping behaviors without the help of store staff. And can make buying decision even have left shopping mall as a online mode. Scheme 4. Store managers can record the products and the environment of store with 360 camera and update to website. Then customers can browse the virtual space with VR glasses. That make customers can have the real shopping experience without being in the store. In this study, have presented schemes of digital media in commercial space. But there are various of commercial space. In this study was presented schemes for shopping mall by searching fashion shopping behaviors of users. And look forward the researches about specific space setting and other type of commercial space for space development.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.127-133
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• 2021

A recent study of people physically falling focused on analyzing the motions of the falls using a recurrent neural network (RNN) and a deep learning approach to get good results from detecting 2D human poses from a single color image. In this paper, we investigate a detection method for estimating the position of the head and shoulder keypoints and the acceleration of positional change using the skeletal keypoints information extracted using PoseNet from an image obtained with a low-cost 2D RGB camera, increasing the accuracy of judgments about the falls. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion-analysis method. A public data set was used to extract human skeletal features, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than a conventional, primitive skeletal data-use method.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.67-75
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• 2022

Medical information is variously generated not only from medical devices but also from electronic devices. Recently, related convergence technologies from big data collection in healthcare to medical AI products for patient's condition analysis are rapidly increasing. However, there are difficulties in applying them because of independent developmental procedures. In this paper, we propose an intelligent hospital information system (iHIS) model to simplify and integrate research, development and application of medical AI technology. The proposed model includes (1) real-time patient data management, (2) specialized data management for medical AI development, and (3) real-time monitoring for patient. Using this, real-time biometric data collection and medical AI specialized data generation from patient monitoring devices, as well as specific AI applications of camera-based patient gait analysis and brain MRA-based cerebrovascular disease analysis will be introduced. Based on the proposed model, it is expected that it will be used to improve the HIS by increasing security of data management and improving practical use through consistent interface platformization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.207-215
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• 2022

This research has been focused on accessing precision and accuracy of UAV (Unmanned Aerial Vehicle)-derived 3-D surveying coordinates. To this end, a highly precise and accurate testing control network had been established by GNSS (Global Navigation Satellite Systems) campaign and its network adjustment. The coordinates of the ground control points and the check points were estimated within 1cm accuracy for 95% of the confidence level. FC330 camera mounted on DJI Phantom 4 repeatedly took aerial photos of an experimental area seven times, and then processed them by two widely used software packages. To evaluate the precision and accuracy of the aerial surveys, 3-D coordinates of the ten check points which automatically extracted by software were compared with GNSS solutions. For the 95% confidence level, the standard deviation of two software's result is within 1cm, 2cm, and 4cm for the north-south, east-west, and height direction, and RMSE (Root Mean Square Error) is within 9cm and 8cm for the horizontal, vertical component, respectively. The interest is that the standard deviation is much smaller than RMSE. The F-ratio test was performed to confirm the statistical difference between the two software processing results. For the standard deviation and RMSE of most positional components, exception of RMSE of the height, the null hypothesis of the one-tailed tests was rejected. It indicates that the result of UAV photogrammetry can be different statistically based on the processing software.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.211-220
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• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.119-126
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• 2019

Watching movies is common on a big screen like a theater or on a big-screen TV. nowadays, small platform such as mobile devices is increasing rapidly for watch a movie. These changes are deeply related to the advent of Internet-based video streaming services such as OTT. OTT's development has provided in free video viewing system without using the set-top box is free from the limitations of time and space. Leading the market is Netflix[1], which started its business with Internet-based DVD rental service. Netflix, which is growing in tandem with the mobile market, had 193.26[2] million members as of the end of 2018. Other OTT participating companies include content-based Pooq, TVing, platform-based Olleh TV Mobile, Oksusu and LTE video portal. The size of such new growth projects has grown gradually, with 25.4 percent of all smartphone users currently watching video content with small mobile devices. Therefore, de-largeization, it is thought that visual language is needed for viewing small mobile devices that are capable of OTT services. To this end, this paper will identify the problem in viewing popular video content with small mobile devices and Survey and study its impact on viewers using the questionnaire.