• International Journal of Internet, Broadcasting and Communication
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• 제10권2호
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• pp.13-18
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• 2018

Drones are controlled by the remote pilot from the ground stations using the radio control or autonomously following the pre-programmed flight plans. In this paper, we develop a method and an optimal path search system for providing 3D augmented reality flight (ARF) images for safe and efficient flight control of drones. The developed system consisted of the drone, the ground station and user terminals, and the optimal path search server. We use the Dijkstra algorithm to find the optimal path considering the drone information, flight information, environmental information, and flight mission. We generate a 3D augmented reality flight (ARF) image overlaid with the path information as well as the drone information and the flight information on the flight image received from the drone. The ARF image for adjusting the drone is generated by overlaying route information, drone information, flight information, and the like on the image captured by the drone.

• 디지털융복합연구
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• 제16권4호
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• pp.313-319
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• 2018

본 연구는 최근 방송, 영화 등에 활발하게 사용되고 있는 드론의 무빙 영상이 수용자의 몰입도와 흥미 유발, 감정상태 등에 미치는 영향을 살펴본 실험 연구이다. 그동안 미디어 영상 효과 연구들은 영상의 움직임이 스토리 자체에 내재되어 있는 느낌을 주기 위해서 카메라의 움직임을 자제하는 것이 좋으며, 카메라의 움직임이 오히려 수용자의 자연스러운 시청에 방해가 될 수 있다고 주장하고 있다. 본 연구에서는 드론의 움직이는 영상이 시청자의 몰입도, 흥미 유발, 감정 상태 등에 어떤 영향을 미치는지 알아보기 위해서, 대학생들을 두 그룹으로 나누고, 한 그룹의 피실험자들에게는 무빙 중심으로 편집된 드론 영상물을 보여주고, 다른 한 그룹의 피실험자들에게는 호버링 중심으로 편집된 드론 영상물을 각각 보여준 다음, 설문조사를 통해 이들이 느낀 몰입도, 흥미도, 감정상태 등을 측정하고, 측정한 결과를 변량 분석하였다. 분석 결과, 드론의 움직임이 있는 영상물을 감상한 피실험자들은 드론의 움직임이 없는 영상물을 감상한 피실험자들에 비해, 흥미를 더 많이 느끼고, 긍정적인 감정상태를 더 많이 느낀것으로 나타났다. 그러나 드론의 무빙과 피실험자들의 몰입도 간에는 서로 관련이 없는 것으로 나타났다.

• Journal of Ecology and Environment
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• 제41권4호
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• pp.114-119
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• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• 한국측량학회지
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• 제36권3호
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• pp.197-202
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• 2018

Drone has been continuously studied in the field of geography and remote sensing. The basic researches have been actively carried out before the utilization in the field of photogrammetry. In Korea, it is necessary to study the actual way of research in accordance with the drone utilization environment. In particular, analysis on the characteristics of DSM (Digital Surface Model) generated through drone are needed. In this study, the characteristic of drone DSM as a data acquisition method was analyzed for coastal management. The coastal area was selected as the study area, and data was acquired by using drone. As a result of the study, the terrain model and the ortho image of coastal area were produced. The accuracy of UAV (Unmanned Aerial Vehicle) results were very high about 10cm at check points. However, concavo-convex shapes appeared in very flat areas such as tidal flats and roads. To correct this terrain model distortion, a new terrain model was created through data processing and the results were evaluated. If additional studies are carried out and the construction and analysis of terrain model using drone image is done, drone data for coastal management will be available.

• 한국측량학회지
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• 제39권2호
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• pp.81-91
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• 2021

Drone related research has been increasing recently due to the development and distribution of commercial unmanned aerial vehicles. However, most of the previous studies focused on the accuracy and utility of drone surveying. For drones, the resolution of the result is determined according to the flight altitude, but since 70% of Korea is mountainous, it is necessary to analyze the quality of the drone image according to the flight plan. In this study, the quality of drone photogrammetry results according to flight plans was analyzed. The flight plan was established by fixed altitude and considering the height of the terrain. Images were acquired for both cases and data was processed to generate ortho images. As a result of evaluating the accuracy of the generated ortho image, the accuracy was found to be -0.07 ~ 0.09m. The accuracy of Case I and Case II did not show a significant difference, but for RMSE, Case I showed a good value. These results indicate that the drone flight plan affects the quality of the results. Also, when flying at a fixed altitude, II showed a lower value than the originally set overlap according to the altitude of the object. In future surveys using drones, flight planning taking into account the height of the object will contribute to the improvement of the quality of the results.

• 한국정보통신학회논문지
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• 제22권3호
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• pp.491-498
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• 2018

드론(dron)은 무인항공기(UVA : Unmanned Aerial Vehicle)로 조종사가 탑승하지 않고 원격으로 조정하거나 사전에 프로그램으로 입력된 경로를 스스로 비행하는 비행물체를 의미한다. 처음 군사적 목적으로 개발된 드론은 현재 다양한 용도로 사용할 수 있도록 개발되어 농업 산업을 비롯하여 여가활용, 물류 서비스, 인명 구조 분야에 이르기 까지 다양한 분야에서 사용되고 있다. 이러한 분야 중 드론에 카메라를 장착하여 개발된 촬영용 드론은 현재 영화나 방송분야를 넘어 다양한 영상콘텐츠 제작 분야에서 활발히 사용되고 있다. 본 논문은 촬영을 목적으로 하는 드론의 특징에 대하여 살펴보고 드론의 비행이나 드론을 활용한 촬영기법에 대하여 다룬다. 특히 영상콘텐츠 제작 분야에서 사용되는 촬영용 드론의 운용에 대하여 살펴본 후 기존의 영상촬영에서 사용되는 다양한 카메라 워킹을 드론을 사용하여 촬영하는 방법에 대하여 제안하고 논의하는데 그 목적을 둔다.

• 대한임베디드공학회논문지
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• 제14권3호
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• pp.157-163
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• 2019

As the drone industry has grown greatly in recent years, drones are being used or developed in many industrial fields such as image shooting, pesticide application, delivery service, food delivery etc. In this paper, therefore, we developed a program that takes a user's desired area at a certain height using a camera-equipped drone and obtains the area of the zone the user wants through image processing. The first user selects an area or a path. Afterwards, the drone flies and takes pictures, and then measures the user's needs. A digital image taken at a constant height and with the same resolution is composed of pixels, the area can be calculated easily if we know the number of pixels in the zone the user wants. Particularly, it is easy to calculate the area of various shaped zones, not terrain shapes such as triangles and squares. In addition, the total area of specific places of the entire zone can be calculated. With the program of this paper, anyone can easily calculate the area of the place the user wants using a drone rather than calculating the area through difficult formulas or specialized equipment.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.30-30
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• 2018

제방 매핑 연구는 제방 안전도 측정을 위해 중요하며, 드론 영상은 실시간 제방 지도를 만들기 위해 활용될 수 있다. 본 연구에서는 하천유역을 촬영한 드론 영상을 이용하여 제방 매핑 연구를 진행하였다. 우선 테스트 베드의 하천유역을 촬영한 드론 영상을 수집한다. 그리고 드론 영상을 이용하여 사진측량/영상처리 기법을 기반으로 3차원 디지털 표고모델(DEM)과 정사영상을 제작한다. 최종적으로 수동/자동화 기법을 이용하여 제방 표면에 존재하는 중요한 객체(둑마루, 제방법선, 비탈경사면, 침식지역 등)를 디지털 표고모델과 정사영상으로부터 탐지한다. 추후 연구에서는 드론 영상으로부터 중요한 객체를 탐지할 수 있는 자동화 기술 개발을 목표로 한다.

• 로봇학회논문지
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• 제12권4호
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• pp.425-431
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• 2017

As drones gain more popularity these days, drone detection becomes more important part of the drone systems for safety, privacy, crime prevention and etc. However, existing drone detection systems are expensive and heavy so that they are only suitable for industrial or military purpose. This paper proposes a novel approach for training Convolutional Neural Networks to detect drones from images that can be used in embedded systems. Unlike previous works that consider the class probability of the image areas where the class object exists, the proposed approach takes account of all areas in the image for robust classification and object detection. Moreover, a novel loss function is proposed for the CNN to learn more effectively from limited amount of training data. The experimental results with various drone images show that the proposed approach performs efficiently in real drone detection scenarios.

• Ecology and Resilient Infrastructure
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• 제9권3호
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• pp.154-162
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• 2022

지상표정점을 이용하지 않고도 동영상에 기록된 위치정보 (GPS 자료)만을 이용하여 드론으로 촬영한 동영상에서 절대위치의 유속을 산정할 수 있는 방법을 개발하였다. 이 방법은 드론 동영상에서 있는 GPS 정보를 이용하여 드론의 이동방향과 영상이 향하는 방향을 결정하고, 각 영상점을 물리적인 전역좌표계 (UTM 좌표계)로 변환하였다. 그 다음 시작프레임과 종료프레임을 지정하여 분석할 동영상의 범위를 결정하였다. 지정된 두 프레임의 정보를 이용하여 측정횡단면을 일정간격의 기준프레임 (측정소단면)으로 나누었다. 그리고, 각 측정소단면에서 1초간 영상 (30 프레임)을 모아서 시공간체적을 구성한 뒤 유속을 분석한다. 이렇게 개발된 방법을 기존의 정지비행드론을 이용한 동영상분석법과 비교한 결과 상당히 양호한 결과를 보였다.