• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.328-329
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• 2007

본 논문은 로봇과 같이 외부 음향잡음에 노출되어 있는 상황 하에서, 대면하고 있는 사람이 입술을 움직여 발성하는 경우에만 음성인식 기능이 수행되도록 하기 위한 방안의 일환으로, 입술움직임 영상을 보다 정확히 추적하기 위한 테스트 환경 구현에 관한 것이다. 음성구간 검출과정에서 입술움직임 영상 추적결과의 활용여부는 입술움직임을 얼마나 정확하게 추적할 수 있느냐에 달려있다. 이를 위해 영상 프레임율 동적 제어, 칼라/이진영상 변환, 순간 캡쳐, 녹화 및 재생기능을 구현함으로써, 다각적인 방향에서 입술움직임 영상 추적기능을 확인해 볼 수 있도록 하였다. 음성/영상기능을 연동시킨 결과 약 99.3%의 연동성공율을 보였다.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.159-167
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• 2012

Eye tracking technology tracks human eyes movements to understand user's intention. This technology has been improving slowly and should be used for a variety of occasions now. For example, it enables persons with disabilities to operate a computer with their eyes. This article will show a typical implementation of an eye tracking system for persons with disabilities, after introducing the design principles and specific implementation details of an eye tracking system. The article discussed the realization of self-adapting regulation algorithm in detail. The self-adapting algorithm is based on feedback signal controlling the lens movements to realize automatic focus, and to get a clear eyes image. This CCD camera automatic focusing method has self-adapting capacity for changes of light intensity on the external environment. It also avoids the trouble of manual adjustment and improves the accuracy of the adjustment.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.1-9
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• 2008

In this paper, we proposed automatic face detection and tracking which is robustness in rotation. To detect a face image in complicated background and various illuminating conditions, we used face skin color detection. we used Harris corner detector for extract facial feature points. After that, we need to track these feature points. In traditional method, Lucas-Kanade feature tracker doesn't delete useless feature points by occlusion in current scene (face rotation or out of camera). So we proposed the estimation function, which delete useless feature points. The method of delete useless feature points is estimation value at each pyramidal level. When the face was occlusion, we deleted these feature points. This can be robustness to face rotation and out of camera. In experimental results, we assess that using estimation function is better than traditional feature tracker.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.241-253
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• 2006

In modem societies, a monitoring system is required to automatically detect and track persons from several cameras scattered in a wide area. Combining multiple cameras with non-overlapping views and a tracking technique, we propose a method that tracks automatically the target persons in one camera and transfers the tracking information to other networked cameras through a server. So the proposed method tracks thoroughly the target persons over the cameras. In this paper, we use a person model to detect and distinguish the corresponding person and to transfer the person's tracking information. A movement of the tracked persons is defined on FOV lines of the networked cameras. The tracked person has 6 statuses. The proposed system was experimented in several indoor scenario. We achieved 91.2% in an averaged tracking rate and 96% in an averaged status rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.89-96
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• 2010

In this paper, we proposed a method about improving face tracking efficiency of face detection for AF system using the faces to the ROI. The conventional face detection system detecting faces based skin color uses the ratio of skin pixels of the present frame to detected face regions of the past frame to track the faces. The tracking method is superior in the stability of the regions but it is inferior in the face tracking efficiency. We proposed a face tracking method using the area of the overlapping region in the detected face regions of the past frame and the present frame to improve the tracking efficiency. The proposed face tracking efficiency demonstration was performed by making a film of face detection with face tracking in real-time and using the moving traces of the detected faces.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.851-859
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• 2011

In this paper, we propose the method that automatically extracts the silhouette and the joints of consecutive input image, and track joints to trace object for interaction between human and computer. Also the proposed method presents the action of human being to map human body using joints. To implement the algorithm, we model human body using 14 joints to refer to body size. The proposed method converts RGB color image acquired through a single camera to hue, saturation, value images and extracts body's silhouette using the difference between the background and input. Then we automatically extracts joints using the corner points of the extracted silhouette and the data of body's model. The motion of object is tracted by applying block-matching method to areas around joints among all image and the human's motion is mapped using positions of joints. The proposed method is applied to the test videos and the result shows that the proposed method automatically extracts joints and effectively maps human body by the detected joints. Also the human's action is aptly expressed to reflect locations of the joints

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.490-498
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• 2010

This paper presents an autonomous target tracking approach and technique for transmitting ground control station image periodically for an unmanned aerial vehicle using onboard gimbaled(pan-tilt) camera system. The miniature rotary UAV which was used in this study has a small, high-performance camera, improved target acquisition technique, and autonomous target tracking algorithm. Also in order to stabilize real-time image sequences, image stabilization algorithm was adopted. Finally the target tracking performance was verified through a real flight test.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.4
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• pp.113-117
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• 2007

The study was performed on the development of system in which the bead width can be controlled. In order to control the bead width, we designed the automatic seam tracking device by attaching the probe type strain gauge sensor, motor driving slide and encoder to check the moving distance, and interface card connected MCU(80Cl96KC) upside the speed controllable carriage. Seam tracking experiments were done by changing the bead width. We compared and analyzed the sampling data which were obtained by output voltage of strain gauge sensor and rotary encoder pulse every 50ms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.1-8
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• 2000

This paper describes an algorithm for semantic video object tracking using semi automatic method. In the semi automatic method, a user specifies an object of interest at the first frame and then the specified object is to be tracked in the remaining frames. The proposed algorithm consists of three steps: object boundary projection, uncertain area extraction, and boundary refinement. The object boundary is projected from the previous frame to the current frame using the motion estimation. And uncertain areas are extracted via two modules: Me error-test and color similarity test. Then, from extracted uncertain areas, the exact object boundary is obtained by boundary refinement. The simulation results show that the proposed video object extraction method provides efficient tracking results for various video sequences compared to the previous methods.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.10
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• pp.1234-1243
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• 1988

In this paper, a target tracking algorithm using the centroid of moving edges is presented. It aims to avoid the difficulty of image segmentation in case of extracting the centroid from only one frame. The proposed algorithm can more easily segment the target than the conventional one in images with complex background. Moreover, it can track the target well when the target is occluded by an object. The result of applying it to a real-time target tracker is shown to be comparatively good.