• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.645-653
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• 2020

Recently studies on how to use the UAV (Unmanned Aerial Vehicle) are actively being conducted, and the National Geographic Information Institute published the 『Work Guidelines for Public Surveying of Unmanned Aerial Vehicles』. However, the guidelines do not provide the optimum shooting conditions required for each application. In this study, we tried to find the suitable shooting conditions for the production of 3D (Three-dimensional) spatial information and orthophoto. To this end, 45 experiments were conducted by various altitudes, overlaps, and camera angles within an above ground level of 150m. For evaluating the 3D modeling by shooting conditions, point densities of 9 verification areas were analyzed, and to evaluate the orthophotos, 1/1,000 digital maps were compared. Considering the quality of the output and the processing time for precise 3D construction, an altitude of 50m, an overlap of 70~80%, and a camera angle of 80~90° are suitable as shooting conditions, and an altitude of 100m and camera angle of 80~90° are suitable for orthophoto generation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.890-896
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• 2022

In this paper, gimbal camera control through smart gloves was implemented to increase convenience and accessibility to the control of drones used in various fields. Smart gloves identify human gestures and transmit signals through Bluetooth. The received signal is converted into a signal suitable for the drone through a GCS (Gound Control Station). Signals from smart gloves are expressed in a quaternion method to prevent gimbal locks, but for gimbal cameras, conversion is required to use Roll, Pitch, and Yaw methods. The data conversion mission is performed in the GCS. The GCS transmits an input signal to the control board of the drone through Wi-Fi. The control board generates and outputs the transmitted signal in a PWM manner. The output signal is input to the gimbal camera through the SBUS method and controlled. The input signal of the smart glove averaged 0.093 s and up to 0.099 s to output to the gimbal camera, showing that there was no problem in real-time use.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.287-294
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• 2010

TOF technique is one of the skills that can obtain the object's 3D depth information. But depth image has low resolution and fingertip occupy very small region, so, it is difficult to find the precise fingertip's 3D information by only using depth image from TOF camera. In this paper, we estimate fingertip's 3D location using Arm Model and reliable hand's 3D location information that is modified by hexahedron as hand model. Using proposed method we can obtain more precise fingertip's 3D information than using only depth image.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.72-77
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• 2014

There are two main technologies to implement cloud effect in flight simulator, cloud modeling using particle system and texture mapping. In former case, this approach may cause a low frame rate while unrealistic cloud effect is observed in latter case. To Solve this problem, in this paper, we propose how to apply fog effect into camera to display more realistic cloud effect with high frame rate. The proposed method is tested with massive terrain database environment through implemented software by using OpenSceneGraph. As a result, compared to texture mapping method, the degree of difference on frame rate is 1 or 2Hz while the cloud effect is significantly improved as realistic as particle system.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.212-226
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• 2014

This paper presents the design and implementation of a pipelined architecture and a method for real-time human detection using depth image from a Time-of-Flight (ToF) camera. In the proposed method, we use Euclidean Distance Transform (EDT) in order to extract human body location, and we then use the 1D, 2D scanning window in order to extract human joint location. The EDT-based human extraction method is robust against noise. In addition, the 1D, 2D scanning window helps extracting human joint locations easily from a distance image. The proposed method is designed using Verilog HDL (Hardware Description Language) as the dedicated hardware architecture based on pipeline architecture. We implement the dedicated hardware architecture on a Xilinx Virtex6 LX750 Field Programmable Gate Arrays (FPGA). The FPGA implementation can run 80 MHz of maximum operating frequency and show over 60fps of processing performance in the QVGA ($320{\times}240$) resolution depth image.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.746-749
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• 2002

This paper is introducing a radio control helicopter as a new platform of ground truth measurement. This helicopter is normally used for spraying an agricultural chemical. It can do pinpoint hovering and programing flight using DGPS etc., A spectrometer with dual port can measure ground surface and white reference plate at the same time. And it can also take digital images by digital camera. It is needed to collect ground reflectance information as satellite sensor footprint size for satellite data validation. Generally it is possible to get such ground reflectance by an airplane measurement. But it is high cost and not so easy to make a measurement by airplane. Developed validation system can provide such ground reflectance in low cost and easy.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1073-1075
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• 2019

최근 VR/AR, 자율주행차 등 다양한 응용분야가 주목 받으며 Time of Flight (ToF) 카메라와 같은 사물과 카메라 간의 거리를 측정할 수 있는 3D 카메라를 활용한 연구가 활발히 진행되고 있다. 정확한 영상 정보를 획득하기 위해, ToF 카메라 센서에 의해 발생할 수 있는 노이즈를 모델링하는 것은 필수적이다. 본 논문에서 우리는 ToF 카메라 센서에 의해 발생하는 노이즈를 모델링하기 위해 Skellam 분포를 도입한다. 연속하는 거리 영상의 픽셀 차에 대한 분포를 분석함으로써 Skellam 분포 적용의 타당성을 제시한다. ToF 카메라의 노이즈 모델링을 통해 ToF 카메라 센서에 발생하는 노이즈를 제거하고 출력 영상의 품질을 향상시킬 것으로 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.466-468
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• 2022

3D reconstruction is important issue in many applications such as Augmented Reality (AR), eXtended Reality (XR), and Metaverse. For 3D reconstruction, depth map can be acquired by stereo camera and time-of-flight (ToF) sensor. We used both sensors complementarily to improve the accuracy of 3D information of the data. First, we applied general multi-camera calibration technique which uses both color and depth information. Next, the depth map of the two sensors are fused by 3D registration and reprojection approach. The fused data is compared with the ground truth data which is reconstructed using RTC360 sensor. We used Geomagic Wrap to analysis the average RMSE of the two data. The proposed procedure was implemented and tested with real-world data.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.641-647
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• 2015

This paper proposes a new strategy for a quad-rotor to track a moving object efficiently by using image processing and an extended Kalman filter. The goal of path planning for the quad-rotor is to design an optimal path from the start point to the destination point. To lengthen the freight time of the quad-rotor, an optimal path is required to reduce the energy consumption. To track a moving object, the mark signed on the moving object has been detected by a camera mounted first on the quad-rotor. The center coordinates of the mark and its area are calculated through the blob analysis which is one type of image processing. The mark coordinates are utilized to obtain information on the motion direction and the area of the mark is utilized to recognize whether the object moves backward or forward from the camera on the quad-rotor. In addition, an extended Kalman filter has been applied to predict the direction and speed of the dynamically moving object. Through these schemes, it is aimed that the quad-rotor can track the dynamic object efficiently in terms of flight distance and time. Through the two different route freights of the quad-rotor, the performance of the proposed system has been demonstrated.