• Title/Summary/Keyword: Camera drone

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Characteristics of Drone Broadcasting Camera Moving through Content Analysis Method (내용분석을 통해 본 드론 방송영상의 카메라 움직임 특성 연구)

  • Lim, Hyunchan
    • Journal of Korea Multimedia Society
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    • v.24 no.8
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    • pp.1178-1183
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    • 2021
  • Based on the camera movement on image expression and grammar, this study intended to analyze the characteristics of image expression filmed and broadcasted by drones. This study analyzed drone images using the movement characteristics of existing video cameras as a coding nomenclature. These were intended to examine the differences from existing video grammar and their implications. This study conducted a content analysis using the entire population of drone news footage broadcast for four years in 2015, 2016, 2017 and 2018 by TV Chosun. The size of the screen, camera work, duration of the shot, camera angle, etc. were selected and analyzed. As a result, the drone camera work showed that it uses the most dolly shots in the case of camera movement, followed by the drone camera movement in the order of pan and tilt shots. For zoom, the frequency of use was the smallest. In addition, this study analyzed the size of the screen, duration of the shot, and camera angle of drone. Analysis shows that drones use certain camera movements most frequently, and unlike grandiose modifiers such as "extension of human gaze," drone remains as a supplementary means to enhance the traditional media expression.

A Study on Control of Drone Swarms Using Depth Camera (Depth 카메라를 사용한 군집 드론의 제어에 대한 연구)

  • Lee, Seong-Ho;Kim, Dong-Han;Han, Kyong-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.8
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    • pp.1080-1088
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    • 2018
  • General methods of controlling a drone are divided into manual control and automatic control, which means a drone moves along the route. In case of manual control, a man should be able to figure out the location and status of a drone and have a controller to control it remotely. When people control a drone, they collect information about the location and position of a drone with the eyes and have its internal information such as the battery voltage and atmospheric pressure delivered through telemetry. They make a decision about the movement of a drone based on the gathered information and control it with a radio device. The automatic control method of a drone finding its route itself is not much different from manual control by man. The information about the position of a drone is collected with the gyro and accelerator sensor, and the internal information is delivered to the CPU digitally. The location information of a drone is collected with GPS, atmospheric pressure sensors, camera sensors, and ultrasound sensors. This paper presents an investigation into drone control by a remote computer. Instead of using the automatic control function of a drone, this approach involves a computer observing a drone, determining its movement based on the observation results, and controlling it with a radio device. The computer with a Depth camera collects information, makes a decision, and controls a drone in a similar way to human beings, which makes it applicable to various fields. Its usability is enhanced further since it can control common commercial drones instead of specially manufactured drones for swarm flight. It can also be used to prevent drones clashing each other, control access to a drone, and control drones with no permit.

An Education Plan for Camera Drone (촬영용 드론 교육 방안)

  • Park, Sung-Dae;Han, Kun-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1206-1213
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    • 2021
  • A drone invented for the military has been increased the range of application with the development of relevant technology, and it influences to include the private area. Currently, the use of drone has been increasing in many areas, such as agriculture, unmanned parcel service, production of image contents, and architecture. In 2021, South of Korea, a drone certificate system for drone flight is introduced and on operation. In case of drone flight with the maximum takeoff weight as 2kg or up, the flight experience and practical examination are required, whereas in case of drone lighter than 2kg, the online education qualification is enough to operate it without the flight experience and practical examination. Recently, the drone related accidents have been increasing with the rapidly supply of camera drones with the maximum takeoff weight as less than 2kg. This paper introduces the characteristics of the camera drone to meet burgeoning demand, and discusses an education plan for the camera drone.

Collaborative Obstacle Avoidance Method of Surface and Aerial Drones based on Acoustic Information and Optical Image (음향정보 및 광학영상 기반의 수상 및 공중 드론의 협력적 장애물회피 기법)

  • Man, Dong-Woo;Ki, Hyeon-Seung;Kim, Hyun-Sik
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.7
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    • pp.1081-1087
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    • 2015
  • Recently, the researches of aerial drones are actively executed in various areas, the researches of surface drones and underwater drones are also executed in marine areas. In case of surface drones, they essentially utilize acoustic information by the sonar and consequently have the local information in the obstacle avoidance as the sonar has the limitations due to the beam width and detection range. In order to overcome this, more global method that utilizes optical images by the camera is required. Related to this, the aerial drone with the camera is desirable as the obstacle detection of the surface drone with the camera is impossible in case of the existence of clutters. However, the dynamic-floating aerial drone is not desirable for the long-term operation as its power consumption is high. To solve this problem, a collaborative obstacle avoidance method based on the acoustic information by the sonar of the surface drone and the optical image by the camera of the static-floating aerial drone is proposed. To verify the performance of the proposed method, the collaborative obstacle avoidances of a MSD(Micro Surface Drone) with an OAS(Obstacle Avoidance Sonar) and a BMAD(Balloon-based Micro Aerial Drone) with a camera are executed. The test results show the possibility of real applications and the need for additional studies.

Auto-Tracking Camera Gimbal for Power Line Inspection Drone and its Field Tests on 154 kV Transmission Lines (송전선로 자동추적 카메라 짐벌 및 154 kV 송전선로 현장시험)

  • Kim, Seok-Tae;Park, Joon-Young;Lee, Jae-Kyung;Ham, Ji-Wan
    • KEPCO Journal on Electric Power and Energy
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    • v.5 no.3
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    • pp.149-156
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    • 2019
  • In the field of maintenance of power transmission lines, drones have been used for their patrol and inspection by KEPCO since 2017. This drone technology was originally developed by KEPCO Research Institute, and now workers from four regional offices of KEPCO have directly applied this technology to the drone patrol and inspection tasks. In the drone inspection system, a drone with an optical zooming camera and a thermal camera can fly automatically along the transmission lines by the ground control system developed by KEPCO Research Institute, but its camera gimbal has been remotely controlled by a field worker. Especially the drone patrol and inspection has been mainly applied for the transmission lines in the inaccessible areas such as regions with river-crossings, sea-crossings and mountains. There are often communication disruptions between the drone and its remote controller in such extreme fields of mountain areas with many barriers. This problem may cause the camera gimbal be out of control, even though the inspection drone flies along the flight path well. In addition, interference with the reception of real-time transmitted videos makes the field worker unable to operate it. To solve these problems, we have developed the auto-tracking camera gimbal system with deep learning method. The camera gimbal can track the transmission line automatically, even when the transmitted video on a remote controller is intermittently unavailable. To show the effectiveness of our camera gimbal system, its field test results will be presented in this paper.

Third Party's Legal Interest Protection from Commercialization of Drones -A focus on Decision of the German District Court- (카메라 장착 드론에 대한 지상 제3자의 법익 보호 - 독일의 하급심 판결을 중심으로 -)

  • Kim, Sung-Mi
    • The Korean Journal of Air & Space Law and Policy
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    • v.35 no.1
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    • pp.3-32
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    • 2020
  • With controlling Drones, although it was discussed in the previous study which showed a possibility. Which is personality and property rights of third parties could be violated while operating the drone with a video camera. But It's hard to find out precedents related to drones in Korea. In case of that someone try to control the drone which is equipped with a camera in a yard of neighborhood, the German District Court (Potsdam) considered an operator of drone has little bit of careless to do his duty and admit nonfeasance claim in the owner of the one's property for prevention to repetition of similar situation according to a nonfeasance claim for prevention to Section 1004 (1) sentence 2 of the German Civil Code(BGB). The drone which is equipped with a camera have possibilities to disrupt property and personal rights of the owner. Because a danger in repetition is getting larger regarding the violation of law. Moreover, there is a case that someone shot down the drone which is equipped with a camer. Because it has a risk to interrupt private life and cause some dangerous in our life. The German district court(Riesa) recently have considered that controlling the drone with a camera in private spaces is illegal as a violation of personal life. In addtion to, the action of property owner shot down drone is a legal according to § 228 of the German Civil Code(BGB) which is caleed "Necessity". Although it is difficult to apply to foreign cases directly to Korea, similar cases are likely to be occurred in Korea. The decision of the German District Court showed implications to Korea. As demand for the camera-equipped drone increases in Korea, it is time to discuss specific measures for drone violations.

The Image Contents Production Techniques Using Drone (드론을 이용한 영상콘텐츠 제작기법)

  • Park, Sung-Dae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.3
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    • pp.491-498
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    • 2018
  • As unmanned aerial vehicle(UVA), drone means a flying object that could aviate the route entered by a program in advance or remotely-controlled when a pilot is not on board. Drone that has been initially developed for the military purpose is currently used for diverse areas such as agricultural industry, leisure activity, logistics service, and life-saving area. Out of these areas, the shooting drone equipped with a camera is actively used for diverse image contents production areas including film and broadcasting area. This paper examines the characteristics of drone for the purpose of shooting, and also handles the shooting techniques using drone. Especially, this study aims to suggest and discuss the methods to shoot diverse camera working used by the existing image shooting with the use of drone after examining the operation of shooting drone used for the image contents production area.

Forest Fire Detection System using Drone Streaming Images (드론 스트리밍 영상 이미지 분석을 통한 실시간 산불 탐지 시스템)

  • Yoosin Kim
    • Journal of Advanced Navigation Technology
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    • v.27 no.5
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    • pp.685-689
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    • 2023
  • The proposed system in the study aims to detect forest fires in real-time stream data received from the drone-camera. Recently, the number of wildfires has been increasing, and also the large scaled wildfires are frequent more and more. In order to prevent forest fire damage, many experiments using the drone camera and vision analysis are actively conducted, however there were many challenges, such as network speed, pre-processing, and model performance, to detect forest fires from real-time streaming data of the flying drone. Therefore, this study applied image data processing works to capture five good image frames for vision analysis from whole streaming data and then developed the object detection model based on YOLO_v2. As the result, the classification model performance of forest fire images reached upto 93% of accuracy, and the field test for the model verification detected the forest fire with about 70% accuracy.

Development of a Pixel-based Area Measurement Program Using Drone and Camera Module (카메라 모듈과 드론을 이용한 면적 자동 측정 프로그램 개발)

  • Kim, Jung Hwan;Kim, Shik
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.3
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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.

A Study on the Image-based Automatic Flight Control of Mini Drone (미니드론의 영상기반 자동 비행 제어에 관한 연구)

  • Sun, Eun-Hey;Luat, Tran Huu;Kim, Dongyeon;Kim, Yong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.6
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    • pp.536-541
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    • 2015
  • In this paper, we propose a the image-based automatic flight control system for the mini drone. Automatic flight system with a camera on the ceiling and markers on the floor and landing position is designed in an indoor environment. Images from the ceiling camera is used not only to recognize the makers and landing position but also to track the drone motion. PC sever identifies the location of the drone and sends control commands to the mini drone. Flight controller of the mini drone is designed using state-machine algorithm, PID control and way-point position control method. From the, The proposed automatic flight control system is verified through the experiments of the mini drone. We see that known makers in environment are recognized and the drone can follows the trajectories with the specific ㄱ, ㄷ and ㅁ shapes. Also, experimental results show that the drone can approach and correctly land on the target positions which are set at different height.