• Journal of the Semiconductor & Display Technology
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• v.13 no.1
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• pp.27-33
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• 2014

Video from unmanned aerial vehicle (UAV) is influenced by natural environments due to the light-weight UAV, specifically by winds. Thus UAV's shaking movements make the video shaking. Objective of this paper is making a stabilized video by removing shakiness of video acquired by UAV. Stabilizer estimates camera's motion from calculation of optical flow between two successive frames. Estimated camera's movements have intended movements as well as unintended movements of shaking. Unintended movements are eliminated by smoothing process. Experimental results showed that our proposed method performs almost as good as the other off-line based stabilizer. However estimation of camera's movements, i.e., calculation of optical flow, becomes a bottleneck to the real-time stabilization. To solve this problem, we make parallel stabilizer making average 30 frames per second of stabilized video. Our proposed method can be used for the video acquired by UAV and also for the shaking video from non-professional users. The proposed method can also be used in any other fields which require object tracking, or accurate image analysis/representation.

• Computers and Concrete
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• v.31 no.5
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• pp.457-468
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• 2023

Buildings, bridges, and dams are examples of civil infrastructure that play an important role in public life. These structures are prone to structural variations over time as a result of external forces that might disrupt the operation of the structures, cause structural integrity issues, and raise safety concerns for the occupants. Therefore, monitoring the state of a structure, also known as structural health monitoring (SHM), is essential. Owing to the emergence of the fourth industrial revolution, next-generation sensors, such as wireless sensors, UAVs, and video cameras, have recently been utilized to improve the quality and efficiency of building forensics. This study presents a method that uses a target-based system to estimate the dynamic displacement and its corresponding dynamic properties of structures using UAV-based video. A laboratory experiment was performed to verify the tracking technique using a shaking table to excite an SDOF specimen and comparing the results between a laser distance sensor, accelerometer, and fixed camera. Then a field test was conducted to validate the proposed framework. One target marker is placed on the specimen, and another marker is attached to the ground, which serves as a stationary reference to account for the undesired UAV movement. The results from the UAV and stationary camera displayed a root mean square (RMS) error of 2.02% for the displacement, and after post-processing the displacement data using an OMA method, the identified natural frequency and damping ratio showed significant accuracy and similarities. The findings illustrate the capabilities and reliabilities of the methodology using UAV to evaluate the dynamic properties of structures.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.49-56
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• 2008

Image registration is one of the critical techniques of image mosaic which has many applications such as generating panoramas, video monitoring, image rendering and reconstruction, etc. The fundamental tasks of image registration are point features extraction and tracking which take much computation time. KLT(Kanade-Lucas-Tomasi) feature tracker has proposed for extracting and tracking features through image sequences. The aim of this study is to demonstrate the usage of effective and robust KLT feature detector and tracker for an image registration using the sequence image frames captured by UAV video camera. In result, by using iterative implementation of the KLT tracker, the features extracted from the first frame of image sequences could be successfully tracked through all frames. The process of feature tracking in the various frames with rotation, translation and small scaling could be improved by a careful choice of the process condition and KLT pyramid implementation.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.400-405
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• 2006

In this paper, we propose a moving object tracking algorithm by using motion estimation in UAV(Unmanned Aerial Vehicle) video. Proposed algorithm is based on generation of initial image from detected reference image, and tracking of moving object under the time-varying image. With a series of this procedure, tracking process is stable even when the UAV camera sways by correcting position of moving object, and tracking time is relatively reduced. A block matching algorithm is also utilized to determine the similarity between reference image and moving object. An experimental result shows that our proposed algorithm is better than the existing full search algorithm.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.131-138
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• 2020

In this paper, we analyze the delay phenomenon that can occur when controlling an unmanned aerial vehicle using a camera and describe a solution to solve the phenomenon. The group of pictures (GOP) value is changed in order to reduce the delay according to the frame data size that can occur in the moving image data transmission. The appropriate GOP values were determined through experimental data accumulation and validated through camera self-test, system integration laboratory (SIL) verification test and system integration test.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.342-351
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• 2010

UAV (Unmanned Aerial Vehicle) have an INS(Inertial Navigation System) equipment and also have an electro-optical Equipment for mission. This paper proposes the vision based attitude estimation algorithm using Kalman Filter and Optical flow for UAV. Optical flow is acquired from the movie of camera which is equipped on UAV and UAV's attitude is measured from optical flow. In this paper, Kalman Filter has been used for the settlement of the low reliability and estimation of UAV's attitude. Algorithm verification was performed through experiments. The experiment has been used rate table and real flight video. Then, this paper shows the verification result of UAV's attitude estimation algorithm. When the rate table was tested, the error was in 2 degree and the tendency was similar with AHRS measurement states. However, on the experiment of real flight movie, maximum yaw error was 21 degree and Maximum pitch error was 7.8 degree.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.194-203
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• 2021

Virtual reality is being increasingly used for healing and therapy for mental health. In this study, we developed VR-based immersive content that enables virtual travel without the limitations of time and physical conditions. We aim to develop and produce VR content for relaxation and meditation using the beautiful natural scenery. To make realistic and immersive content, we took a video of natural sceneries with a small UAV connected to a VR camera. The content was developed through stitching, video editing and post-processing of the initially captured video data, and then the created VR video was inserted into the VR device. The produced content will be helpful for stress and used to heal the mind and body of exhausted modern people by providing the place with great scenery and sound in an immersive way at any time.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.124-132
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• 2017

With the growth of interest in the UAVs, the study of the UAV collision avoidance is in progress. Lidar, Video camera, laser sensor, and ultrasonic sensor may be utilized for collision avoidance of UAV. In this paper, the characteristics of MB 1230 ultrasonic sensor is analyzed through the experiment. When concurrently using multitudinous ultrasonic sensors, ultrasonic sensors do not generate correct measurement values. To solve ultrasonic sensor interference, sequentially transmitting ultrasonics signal is suggested by using 'Enable' signal input of ultrasonic sensor, so by activating each ultrasonic sensor gradually. This proposed solution is also verified by experimentation.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.137-148
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• 2017

Recently, researchers are actively addressed to utilize Unmanned Aerial Vehicles(UAV) for military and industry applications. One of these applications is to trace the preceding flight when it is necessary to track the route of the suspicious reconnaissance aircraft in secret, and it is necessary to estimate the attitude of the target flight such as Roll, Yaw, and Pitch angles in each instant. In this paper, we propose a method for estimating in real time the attitude of a target aircraft using the video information that is provide by an external camera of a following aircraft. Various image processing methods such as color space division, template matching, and statistical methods such as linear regression were applied to detect and estimate key points and Euler angles. As a result of comparing the X-plane flight data with the estimated flight data through the simulation experiment, it is shown that the proposed method can be an effective method to estimate the flight attitude information of the previous flight.