• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.79-94
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• 2007

In the ubiquitous computing age which uses a high quantity network, mobile devices such as wearable and hand-held ones with a small tamers and a wireless communication module will be widely used in near future. Thus, a lot of researches about an augmented game on mobile devices have been attempted recently. The existing augmented games used a traditional 'backpack' system and a pattern marker. The 'backpack' system is expensive, cumbersome and inconvenient to use, and because of the pattern marker, it is only possible to play the game in the previously installed palace. In this paper, we propose an augmented game called Flying Cake using a face region to create the virtual object(character) without the pattern marker, which manually indicates an overlapped location of the virtual object in the real world, on a small and mobile PDA instead of the cumbersome hardware. Flying Cake is an augmented shooting game. This game supplies us with two types: 1) a single player which attacks a virtual character on images captured by a camera in an outdoor physical area, 2) dual players which attack the virtual character on images which we received through a wireless LAN. We overlap the virtual character on the face region using a face detection technique, and users play Flying Cake though attacking the virtual character. Flying Cake supplies new pleasure to flayers with a new game paradigm through an interaction between the user in the physical world captured by the PDA camera and the virtual character in a virtual world using the face detection.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.318-324
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• 2017

We introduced a stereo camera on the aircraft to detect flight objects and to estimate the 3D position of them. The Saliency map algorithm based on PCT was proposed to detect a small object between clouds, and then we processed a stereo matching algorithm to find out the disparity between the left and right camera. In order to extract accurate disparity, cost aggregation region was used as a variable region to adapt to detection object. In this paper, we use the detection result as the cost aggregation region. In order to extract more precise disparity, sub-pixel interpolation is used to extract float type-disparity at sub-pixel level. We also proposed a method to estimate the spatial position of an object by using camera parameters. It is expected that it can be applied to image - based object detection and collision avoidance system of autonomous aircraft in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.580-585
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• 2005

A QRT(Quad-Rotor Type) hovering robot system is developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV(Unmanned Aerial Vehicle) is equipped with four propellers driven by each electric motor, an embedded controller using a DSP, INS(Inertial Navigation System) using 3-axis rate gyros, a CCD camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. The developed hovering robot shows stable flying performances under the adoption of RIC(Robust Internal-loop Compensator) based disturbance compensation and the vision based localization method. The UAV can also avoid obstacles using eight IR and four ultrasonic range sensors. The VTOL(Vertical Take-Off and Landing) flying object flies into indoor fire spots and sends the images captured by the CCD camera to the operator. This kind of small-sized UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.27-33
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• 2020

Recently, visual object detection and tracking has become a vital role in many different applications. It spans various applications like robotics, video surveillance, and intelligent vehicle navigation. Especially, in current situation where the use of UAVs is expanding widely, detection and tracking to soot down illegal UAVs flying over the sky at airports, nuclear power plants and core facilities is becoming a very important task. The remarkable method in object tracking is correlation filter based tracker like KCF (Kernelized Correlation Filter). But it has problems related to target drift in tracking process for long-term tracking. To mitigate the target drift problem in video surveillance application, we propose a tracking method which uses KCF, adaptive thresholding and Kalman filter. In the experiment, the proposed method was verified by using monochrome video sequences which were obtained in the operational environment of UAV.