• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.313-315
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• 2011

Smart phone camera module are mounted on the focus are 2 types depending on the behavior. AF (Auto focus) camera module and the FF (Fixed focus) camera module two are different types. AF camera module to move the location of the lens and is a way to automatically focus, FF camera module lens position of the focus is the way to a fixed state. EDOF camera module the location of the lens as a frozen state EDOF AF module using the algorithm to focus on applied technology is a module. In this paper, optimization EDOF camera module implementation of the resolution.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1160-1166
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• 2007

This paper presents the design and implementation of an embedded image stabilization control system for a mobile phone with a built-in camera. Image stabilization is a family of techniques for reducing image blur resulting from minute camera shake due to hand-held shooting, thereby allowing the use of shutter speeds slower than values normally required to obtain sharp images. A mechanical image stabilizer mechanism developed for a camera mobile phone is introduced and a digital control system as a part of the image stabilization system is designed and implemented on an 8-bit microcontroller with integer arithmetic in C. This paper focuses primarily on issues that need to be taken into consideration for fixed-point implementation of the digital controller. Several experimental results are presented to demonstrate the performance of the implemented image stabilization control system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.277-277
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• 2000

This paper's purpose obtain information of three dimension using a camera. This system embody to know the height of object using triangle method between reference point of circumstance and object. As I use java program, it is possible to make system regardless of operating system, set up the system. By using comportable USB port camera, we used to everywhere without the capture board. We can use the internet by using the java's JMF and applet everywhere, we regard the camera as fixed.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.202-205
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• 2000

In this paper we propose an algorithm that detects, tracks a moving object, and classify whether it is human from the video clip captured under the fixed video camera. It detects the outline of the moving object by finding out the local maximum points of the modulus image, which is the magnitude of the motion vectors. It also estimates the size and the center of the moving object. When the object is detected, the algorithm discriminates whether it is human by segmenting the face. It is segmented by searching the elliptic shape using Hough transform and grouping the skin color region within the elliptic shape.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.650-657
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• 2012

An effective dual-mode camera system(a passive wide-angle camera and a pan-tilt-zoom camera) is proposed in order to improve the performance of visual surveillance. The fixed wide-angle camera is used to monitor large open areas, but the moving objects on the images are too small to view in detail. And, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a specific moving target. However, its FOV (Field of View) is limited when zooming in on a specific target. Therefore, the cooperation of wide-angle and PTZ cameras is complementary. In this paper, we propose an automatic initial set-up algorithm and coordinate transform method from the wide-angle camera coordinate to the PTZ one, which are necessary to achieve the cooperation. The automatic initial set-up algorithm is able to synchronize the views of two cameras. When a moving object appears on the image plane of a wide-angle camera after the initial set-up positioning, the obtained values of the wide-angle camera should be transformed to the PTZ values based on the coordinate transform method. We also develope the PTZ control method. Various in-door and out-door experiments show that the proposed dual-camera system is feasible for the effective visual surveillance.

• ETRI Journal
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• v.26 no.3
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• pp.269-272
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• 2004

We propose an efficient scheme for camera motion characterization in MPEG-compressed video. The proposed scheme detects six types of basic camera motions through threshold-based qualitative interpretation, in which fixed thresholds are applied to motion model parameters estimated from MPEG motion vectors (MVs). The efficiency and robustness of the scheme are validated by the experiment with real compressed video sequences.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.301-312
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• 2005

Three different cases should be considered for motion tracking: moving object with fixed camera, fixed object with moving camera and moving object with moving camera. Two methods are widely used for motion tracking: the optical flow method and the difference frame method. The optical new method is mainly used when either one, object or camera is fixed. This method tracks object using time-space vector which compares object position frame by frame. This method requires heavy computation, and is not suitable for real-time monitoring system such as DVR(Digital Video Recorder). The different frame method is used for moving object with fixed camera. This method tracks object by comparing the difference between background images. This method is good for real-time applications because computation is small. However, it is not applicable if the camera is moving. This thesis proposes and implements the motion tracking system using the difference frame method with PTZ(Pan-Tilt-Zoom) control. This system can be used for moving object with moving camera. Since the difference frame method is used, the system is suitable for real-time applications such as DVR.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.76-84
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• 2008

This paper is mainly concerned with the vision-based attitude stabilization of a quad-rotor UAV. The methods for attitude control rely on computing the roll and pitch angles of the vehicle from a two-camera vision system. One camera is attached to the body-fixed x-axis and the other to the body-fixed y-axis. The attitude computation for the quad-rotor UAV is performed by image processing consisting of Canny edge and Hough line detection. A proportional and integral controller is employed for the attitude hold autopilot. In this paper, the quad-rotor UAV is modeled by 6-DOF nonlinear equations of motion that includes rotor aerodynamics with blade element theory. The performance of the proposed method is evaluated through 3D environmental numerical simulations.

• Journal of the Optical Society of Korea
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• v.20 no.5
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• pp.633-640
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• 2016

In a dual lens stereoscopic camera, a convergence point determines the stereopsis effects of a video. When a user zooms an object, a convergence point is fixed since it is not coupled with a zoom function. Due to the fixed convergence point, it is possible for a zoom to cause the excessive binocular disparity resulting in visual discomfort. In this paper, to solve this problem, we build the relational model including all phenomena possible to arise and propose the adjustment methods of a convergence point by the positions of a focus, an object and a convergence point. We also evaluate the experiments measuring a binocular disparity and the subjective test to investigate the visual comfort. The results show that one of the proposed methods produced more comfortable 3D images to viewers than the others.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.5-77
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• 2001

A Robot vision system with a visual skill so as take information for arbitrary target or object has been applied to auto-inspection and assembling system. It catches the moving target with the manipulator by using the information from the vision system. The robot needs some information where the moving object will place after certain time. A camera is fixed on a robot manipulator, not on the fixed support outside of the robot. It secures wider working area than the fixed camera, and it dedicates to auto scanning of the object. It computes some information on the object center, angle and speed by vision data, and can guess grabbing spot by arriving time. When the location ...