• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.175-182
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• 2020

The non-contact eye tracking is a nonintrusive human-computer interface providing hands-free communications for people with severe disabilities. Recently. it is expected to do an important role in non-contact systems due to the recent coronavirus COVID-19, etc. This paper proposes a novel approach for an eye mouse using an eye tracking method based on a context-aware based AdaBoost multi-region classifier and ASSL algorithm. The conventional AdaBoost algorithm, however, cannot provide sufficiently reliable performance in face tracking for eye cursor pointing estimation, because it cannot take advantage of the spatial context relations among facial features. Therefore, we propose the eye-region context based AdaBoost multiple classifier for the efficient non-contact gaze tracking and mouse implementation. The proposed method detects, tracks, and aggregates various eye features to evaluate the gaze and adjusts active and semi-supervised learning based on the on-screen cursor. The proposed system has been successfully employed in eye location, and it can also be used to detect and track eye features. This system controls the computer cursor along the user's gaze and it was postprocessing by applying Gaussian modeling to prevent shaking during the real-time tracking using Kalman filter. In this system, target objects were randomly generated and the eye tracking performance was analyzed according to the Fits law in real time. It is expected that the utilization of non-contact interfaces.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1479-1488
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• 2022

Accidents in which oil spills occur intermittently in the ocean due to ship collisions and sinkings. In order to prepare prompt countermeasures when such an accident occurs, it is necessary to accurately identify the current status of spilled oil. To this end, the Coast Guard patrols the target area with a fixed-wing airplane or helicopter and checks it with the naked eye or video, but it was difficult to determine the area contaminated by the spilled oil and its exact location on the map. Accordingly, this study develops a technology for direct ortho-rectification by automatically geo-referencing aerial images collected by the Coast Guard without individual ground reference points to identify the current status of spilled oil. First, meta information required for georeferencing is extracted from a visualized screen of sensor information such as video by optical character recognition (OCR). Based on the extracted information, the external orientation parameters of the image are determined. Images are individually orthorectified using the determined the external orientation parameters. The accuracy of individual orthoimages generated through this method was evaluated to be about tens of meters up to 100 m. The accuracy level was reasonably acceptable considering the inherent errors of the position and attitude sensors, the inaccuracies in the internal orientation parameters such as camera focal length, without using no ground control points. It is judged to be an appropriate level for identifying the current status of spilled oil contaminated areas in the sea. In the future, if real-time transmission of images captured during flight becomes possible, individual orthoimages can be generated in real time through the proposed individual orthorectification technology. Based on this, it can be effectively used to quickly identify the current status of spilled oil contamination and establish countermeasures.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.483-490
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• 2021

Due to the recent increase in various problems from underground development in urbanized areas, accurate underground facility information management is highly needed. Therefore, in this study, in order to utilize the Integration Map of Underground Goespatial Information in real time on-site, the function of comparing the mutual location of the GPR (Ground Penetration Radar) sensing data and the Integration Map of Underground Goespatial Information, and function of analyze underground facilities, and function of converting surveying data into a shape file through position correction & attribute editing in a 3D space, and the function of submitting the shape file to the Integration Map of Underground Goespatial Information mobile center was defined and developed as a program. In addition, for the on-site application test of the development program, scenarios used at the underground facility real-time survey site and GPR exploration site were derived, and four sites in Seoul were tested to confirm that the use scenario worked properly. Through this, the on-site utilization of the program developed in this study could be confirmed, and it would contribute to the confirmation of the quality of Shape-file and the "update automation" of "Integration Map of Underground Goespatial Information". In addition, it is expected that the development program will be further applied to the Underground Facility Map's Accuracy Improvement Diffusion Project' promoted by the MOLIT (Ministry of Land, Infrastructure, and Transport).

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.711-719
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• 2021

EBS has been producing numerous educational contents with traditional virtual studio production systems since the early 2000s and applied AR video production system in October 2020, twenty-years after. Although the basic concept of synthesizing graphic elements and actual image in real time by tracking camera movement and lens information is similar to the previous one but the newly applied AR video production system contains some of advanced technologies that are improved over the previous ones. Marker tracking technology that enables camera movement free and position tracking has been applied that can track the location stably, and the operating software has been applied with Unreal Engine, one of the representative graphic engines used in computer game production, therefore the system's rendering burden has been reduced, enabling high-quality and real-time graphic effects. This system is installed on a crane camera that is mainly used in a crane shot at the live broadcasting studio and applied for live broadcasting programs for children and some of the videos such as program introductions and quiz events that used to be expressed in 2D graphics were converted to 3D AR videos which has been enhanced. This paper covers the effect of introduction and application of the AR video production system on EBS content production and the future development direction and possibility.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.697-702
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• 2023

Recently, with the introduction of drones, a core technology of the 4th industrial revolution, various convergence education using drones is being conducted in school education sites. In particular, drone theory and practice education is being conducted in connection with free semester classes and career exploration. The drone convergence education program has higher learner satisfaction than simple demonstration and practice education, and the learning effect is high due to direct practical experience. However, since practical education is being conducted for a large number of learners, it is impossible to restrict and control the flight of a large number of drones in a limited place. In this paper, we propose a monitoring system that allows the instructor to monitor multiple drones in real time and learners to recognize collisions between drones in advance when multiple drones are operated, focusing on education operated in schools. The communication module used in the experiment was equipped with GPS in Murata LoRa, and the server and client were configured to enable monitoring based on the location data received in real time. The performance of the proposed system was evaluated in an open space, and it was confirmed that the communication signal was good up to a distance of about 120m. In other words, it was confirmed that 25 educational drones can be controlled within a range of 240m and the instructor can monitor them.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.333-341
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• 2022

Despite rapidly increasing demand for fishing, there is a lack of studies and information related to fishing, and there is a limit to obtaining the data on the global distribution of fish resources. Since the existing method of investigating fish resource distribution is designed to collect the fish resource information by visiting the investigation area using a throwing net, it is almost impossible to collect nation-wide data, such as streams, rivers, and seas. In addition, the existing method of measuring the length of fish used a tape measure, but in this study, a FishingTAG's smart measure was developed. When recording a picture using a FishingTAG's smart measure, the length of the fish and the environmental data when the fish was caught are automatically collected, and there is no need to carry a tape measure, so the user's convenience can be increased. With the development of a global fishing application using a FishingTAG's smart measure, first, it is possible to collect fish resource samples in a wide area around the world continuously on a real time basis. Second, it is possible to reduce the enormous cost for collecting fish resource data and to monitor the distribution and expansion of the alien fish species disturbing the ecosystem. Third, by visualizing global fish resource information through the Google Maps, users can obtain the information on fish resources according to their location. Since it provides the fish resource data collected on a real time basis, it is expected to of great help to various studies and the establishment of policies.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.427-436
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• 2009

Digital virtual manufacturing is a technology that aims for the rapid development of products and the verification of production-process in ways that are more efficient by integrating digital models within the entire manufacturing process. These digital models utilize various information technologies, such as 3D CAD and simulations. Mixed reality, which represents graphical objects for only needed parts against real scene, can bring a more enriched sense of reality to an existing virtual manufacturing system that is in a pure virtual environment, and it can reduce the time and money needed for modeling the environment. This paper suggests a method for planning virtual factory layouts based on mixed reality using legacy datathat are already constructed in the real field. To do this, we developed the method to acquire simulation data from legacy data and process this acquired data for visualization based on mixed reality. And then we construct display system based on mixed reality, which can simulate virtual factory layout with processed data. Developed system can reduce errors related with factory layout by verifying the location and application of equipments in advance before arrangement of real ones at the practical job site.

• The Journal of Korean Society for Radiation Therapy
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• v.21 no.1
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• pp.1-7
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• 2009

Purpose: The purpose is to evaluate the accuracy of correcting the targeting error through the Target Location System (TLS) for the location change error of the reference point which arises from the movement or motion of patient during the treatment using the CyberKnife. Materials and Methods: In this test, Gafchromic MD-55 film was inserted into the head and neck phantom to analyze the accuracy of the targeting, and then the 6 MV X-ray of CyberKnife (CyberKnife Robotic Radiosurgery System G4, Accuray, US) was irradiated. End to End (E2E) program was used to analyze the accuracy of targeting, which is provided by Accuray Corporation. To compute the error of the targeting, the test was carried out with the films that were irradiated 12 times by maintaining the distance within the rage of $0{\pm}0.2\;mm$ toward x, y, z from the reference point and maintaining the angle within the rage of $0{\pm}0.2^{\circ}$ toward roll, pitch, yaw, and then with the films which were irradiated 6 times by applying intentional movement. And the correlation in the average value of the reference film and the test film were analyzed through independent samples t-test. In addition, the consistency of dose distribution through gamma-index method (dose difference: 3%) was quantified, compared, and analyzed by varying the distance to agreement (DTA) to 1 mm, 1.5 mm, 2 mm, respectively. Results: E2E test result indicated that the average error of the reference film was 0.405 mm and the standard deviation was 0.069 mm. The average error of the test film was 0.413 mm with the standard deviation of 0.121 mm. The result of independent sampling t-test for both averages showed that the significant probability was P=0.836 (confidence level: 95%). Besides, by comparing the consistency of dose distribution of DTA through 1 mm, 1.5 mm, 2 mm, it was found that the average dose distribution of axial film was 95.04%, 97.56%, 98.13%, respectively in 3,314 locations of the reference film, consistent with the average dose distribution of sagittal film that was 95.47%, 97.68%, 98.47%, respectively. By comparing with the test film, it was found that the average dose distribution of axial film was 96.38%, 97.57%, 98.04%, respectively, at 3,323 locations, consistent with the average dose distribution of sagittal film which was 95.50%, 97.87%, 98.36%, respectively. Conclusion: Robotic CyberKnife traces and complements in real time the error in the location change of the reference point caused by the motion or movement of patient during the treatment and provides the accuracy with the consistency of over 95% dose distribution and the targeting error below 1 mm.