• 전자공학회논문지S
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• 제34S권5호
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• pp.45-51
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• 1997

To trnsmit moving image signals by using an object vased coding technique at the rate of 8kbps~11kbps, it is very important to minimize the bit rates used for the compression of the color information of MF-objects. This paper proposes a hybrid coding method which uses the shpae adaptive coding method and the interframe reference method selectively. Gilge's shape adaptive orthogonal coidng method is utilized for shpae adaptive coding. The interfarame reference method approximates the low-passed signals of the image by gilge's shpae adaptive orthogonalization method and then refers the approximation error signals from the high frequency signal components of th eprevious frame. The proposed method achives the bit rates reduction of 17% compared to the gilge's shape adaptive orthogonalization method and 30% rduction compared to the shape adaptive DCT in average.

• 로봇학회논문지
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• 제2권1호
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• pp.21-28
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권1호
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• pp.46-51
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• 2005

Intelligent Space(ISpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Simulations are carried out to evaluate the proposed performance. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• 전자공학회논문지 IE
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• 제45권2호
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• pp.28-33
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• 2008

본 논문에서는 휴머노이드를 이용한 로봇 축구 시스템을 새롭게 제안하며, 다수의 인간형 로봇을 제어하는 방법과 축구 경기를 하기 위한 전략 알고리즘 등에 대해 기술하였다. 로봇의 위치와 방향을 파악하기 위해서 로봇의 위쪽 어깨 부분에 각각의 로봇을 구분할 수 있는 칼라 태그를 부착하였고, 빠른 위치와 방향 인식을 위해 전용의 PC를 통해 영상인식을 수행하였다. 본 논문에서 제안한 휴머노이드 로봇 축구 시스템은 기존의 바퀴 구동형 축구 로봇을 한 단계 발전시킨 것으로, 앞으로 많은 연구를 통하여, 인간처럼 자율 이동이 가능한 로봇 축구 경기가 가능하리라 본다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.317-320
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• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any clue. We implemented a real-time surveillance system that tracks a moving person using pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• 전자공학회논문지S
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• 제35S권3호
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• pp.93-101
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• 1998

In Integrated Tube Components(ITC) process in themanufacturing of color display tube, we describe the necessity of the convergence measurement method using photo sensors. Compared with methods using 1D or 2D cameras, its characteristics is to use of moving image patterns and fixed sensors. This measurement method is formulated as the measurement problem of the phase difference in phase changing periodic signals. The convergence measurement system using photo sensors, for the good performance, must have a small standard deviation for the repetitive measurement in the same condition and a fast measurement time for thecovergence change. By above two conditions, we proposed the real time measurement algorithm of the pahse difference using fundametal and harmonic in phase changing periodic signals. And, the proposed algorithm is applied to the convergence measurement system.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2018년도 춘계 종합학술대회 논문집
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• pp.53-54
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• 2018

This paper introduces an approach to detect motion areas of stationary objects when the camera slightly moves in the scene by computing optical flow. The flow field is computed by two pyramidal architectures of 5 levels which are built by down-sampling the size of the images by half at each level. Two pyramids of images are built and then optical flow is computed at each level. A warping process combines the information and generates a final flow field after applying edge smoothness and outliers reduction steps. Moreover, we convert the flow vectors in order of magnitude and angle to a color map using a pseudo-color palette. Experimental results in the Middlebury optical flow dataset demonstrate the effectiveness of our method compared to other approaches.

• 반도체디스플레이기술학회지
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• 제16권4호
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• pp.97-102
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• 2017

Object detection and tracking have become one of the most active research areas in the past few years, and play an important role in computer vision applications over our daily life. Many tracking techniques are proposed, and Camshift is an effective algorithm for real time dynamic object tracking, which uses only color features, so that the algorithm is sensitive to illumination and some other environmental elements. This paper presents and implements an effective moving object detection and tracking to reduce the influence of illumination interference, which improve the performance of tracking under similar color background. The implemented prototype system recognizes object using invariant features, and reduces the dimension of feature descriptor to rectify the problems. The experimental result shows that that the system is superior to the existing methods in processing time, and maintains better problem ratios in various environments.

• 한국정보전자통신기술학회논문지
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• 제6권2호
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• pp.81-87
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• 2013

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.115-118
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• 2003

This paper describes a system of detecting multi-views faces and estimating their face poses in an omni-directional camera environment for non-intrusive iris recognition. The paper is divided into two parts; First, moving region is identified by using difference-image information. Then this region is analyzed with face-color information to find the face candidate region. Second part is applying PCA (Principal Component Analysis) to detect multi-view faces, to estimate face pose.