• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.2
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• pp.16-22
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• 2010

This paper proposes the real-time moving object tracking system UAV using color information. Case of object tracking, it have studied to recognizing the moving object or moving multiple objects on the fixed camera. And it has recognized the object in the complex background environment. But, this paper implements the moving object tracking system using the pan/tilt function of the camera after the object's region extraction. To do this tracking system, firstly, it detects the moving object of RGB/HSI color model and obtains the object coordination in acquired image using the compact boundary box. Secondly, the camera origin coordination aligns to object's top&left coordination in compact boundary box. And it tracks the moving object using the pan/tilt function of camera. It is implemented by the Labview 8.6 and NI Vision Builder AI of National Instrument co. It shows the good performance of camera trace in laboratory environment.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.35-41
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• 2012

This paper proposes a moving object detection algorithm for active camera system that can be applied to mobile robot and intelligent surveillance system. Most of moving object detection algorithms based on a stationary camera system. These algorithms used fixed surveillance system that does not consider the motion of the background or robot tracking system that track pre-learned object. Unlike the stationary camera system, the active camera system has a problem that is difficult to extract the moving object due to the error occurred by the movement of camera. In order to overcome this problem, the motion of the camera was compensated by using SURF and Pseudo Perspective model, and then the moving object is extracted efficiently using stochastic Label Cluster transport model. This method is possible to detect moving object because that minimizes effect of the background movement. Our approach proves robust and effective in terms of moving object detection in active camera system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.35-40
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• 1998

This paper describes an automatic recognition method of contents in moving images. The recognition process is carried out by the following two steps. At first, camera works in moving images are analyzed and moving objects are extracted from the moving images. Next, the motion of the object is recognized by pre-procured knowledge. These techniques will be applied to a construction of an efficient image database.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.12
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• pp.1737-1743
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• 2013

This paper proposes the range and velocity of the object estimation method using a moving camera. Structure and motion (SaM) estimation is to estimate the Euclidean geometry of the object as well as the relative motion between the camera and object. Unlike the previous works, the proposed estimation method can relax the camera and object motion constraints. To this end, we arrange the dynamics of moving camera-moving object relative motion model in an appropriate form such that the nonlinear observer can be employed for the SaM estimation. Through both simulations and experiments we have confirmed the validity of the proposed estimation algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.67-76
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• 1997

This ppaer describes the development of the stereo camera system(KASS-1) and the control of the vergence of the stereo camera to fix a gaze on a moving object in real-time using a stereo disparity. The motion energy and the stereo disparity of a moving object from the stereo image are used to control the vergence of stereo camera to keep stereo disparity constant. The disparity from the rotating stereo camera is introduced not only from the moving object but also from the background. In this paper, the background disparity error due to the vergence control of the stereo camera is eliminated by compensation algoithm, and the vergence of steereo camera system can be controlled continuously using the disparity of a moving object only.

• International journal of advanced smart convergence
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• v.2 no.1
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• pp.32-35
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• 2013

In this paper we proposed a PTZ camera system which automatically detect and track moving objects in the image. Once a moving object is detected the PTZ camera traces it in real-time. We proposed the control system which does not depend on camera focusing functionality but uses the object's center, moving direction, distance and speed. We implemented the system with the TI DM6446 DSP chip. The experimental result shows that the system has excellent performance for high speed vehicles.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.145-149
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• 2010

In this paper, we propose a kinematic approach to estimating the real-time moving object. A new scheme for a mobile robot to track and capture a moving object using images of a camera is proposed. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.344-352
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• 2003

An effective algorithm for implementation of which detects moving object from image sequences. predicts the direction of it. and drives the camera in real time is proposed. In static camera, for robust motion detection from a dynamic background scene, the proposed algorithm performs statistical modeling of moving objects and background, and trains the statistical modeling of moving objects and background, and trains the statistical feature of background with the initial parts of sequence which have no moving objects. Active camera moving objects are segmented by following procedure, an improved order adaptive lattice structured linear predictor is used. The proposed algorithm shows robust object tracking results in the environment of static or active camera. It can be used for the unmanned surveillance system, traffic monitoring system, and autonomous vehicle.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.39-46
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• 2016

In this paper, we proposed an application which can conduct to take repetition images for special effect shooting at movies or drama using Bluetooth of smart device. The proposed application can move a camera with motors several times as the same moving after saving of the control data based on the application during specific time using Bluetooth. At the repetition moving, we do not permit to control motors of the camera by person for keeping the same start position and end position after saving the moving data. The camera motors are only moved remotely by saving data of the proposed application. We developed the proposed application and a hardware which works motors with camera to check performance evaluation. Then, we confirmed that the proposed application exactly did the same moving to the motors with camera several times according to saved data. Therefore, because the proposed application can take a same images as control remotely the motors of camera, it will be a useful technology for special effect shooting of movies or dramas.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.71-75
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• 2009

In this paper, we present a real-time method to detect moving objects in a rotating and zooming camera. It is useful for camera surveillance of fixed but rotating camera, camera on moving car, and so on. We first compensate the global motion, and then exploit the displaced frame difference (DFD) to find the block-wise boundary. For robust detection, we propose a kind of image to combine the detections from consecutive frames. We use the block-wise detection to achieve the real-time speed, except the pixel-wise DFD. In addition, a fast block-matching algorithm is proposed to obtain local motions and then global affine motion. In the experimental results, we demonstrate that our proposed algorithm can handle the real-time detection of common object, small object, multiple objects, the objects in low-contrast environment, and the object in zooming camera.