• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.291-297
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• 2018

In this paper, we present an automatic image object tracking system for Studio cameras on the stage. For object tracking, we use the OpenCV-based Python program using PC, Raspberry Pi 3 and mobile devices. There are many methods of image object tracking such as mean-shift, CAMshift (Continuously Adaptive Mean shift), background modelling using GMM(Gaussian mixture model), template based detection using SURF(Speeded up robust features), CMT(Consensus-based Matching and Tracking) and TLD methods. CAMshift algorithm is very efficient for real-time tracking because of its fast and robust performance. However, in this paper, we implement an image object tracking system for studio cameras based CMT algorithm. This is an optimal image tracking method because of combination of static and adaptive correspondences. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the stage in real time.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.211-216
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• 2012

There are two kinks of processes could detect the laser pointer. One is the process which detects the location of the pointer. the other one is a possibility of dividing with the process which converts the coordinate of the laser pointer which is input in coordinate of the monitor. The previous Mean-Shift algorithm is not appropriately for real-time video image to calculate many quantity. In this paper, we proposed the context driven real-time laser pointer detection and tracking. The proposed method is a possibility of getting the result which is fixed from the situation which the background and the background which are complicated dynamically move. In the actual environment, we can get to give constant results when the object come in, when going out at forecast boundary. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the accuracy and the quality of image recognition will be improved the surveillance system.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.159-170
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• 2009

It is very important to extract the expression data and capture a face image from a video for online-based 3D face animation. In recently, there are many researches on vision-based approach that captures the expression of an actor in a video and applies them to 3D face model. In this paper, we propose an automatic data extraction system, which extracts and traces a face and expression data from realtime video inputs. The procedures of our system consist of three steps: face detection, face feature extraction, and face tracing. In face detection, we detect skin pixels using YCbCr skin color model and verifies the face area using Haar-based classifier. We use the brightness and color information for extracting the eyes and lips data related facial expression. We extract 10 feature points from eyes and lips area considering FAP defined in MPEG-4. Then, we trace the displacement of the extracted features from continuous frames using color probabilistic distribution model. The experiments showed that our system could trace the expression data to about 8fps.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.287-295
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• 2010

RTLS used to track the location of object or person in real time. However, if there are a lot of tags and readers, the conventional single RTLS server may fail to estimate location of tags. And if the server cannot receive the tags signal due to pass-loss or NLOS from more than three readers, the server fail to estimate location of tags. In this paper, we propose a special reader which embeds RTLS location engine for distributed RTLS. And by using multi-directional antenna, alleviating multi-path effect and allowing estimate tag's location only using two readers. We also implement the system, we can reduce server packet 16times and get the all results of location estimate in single second. We achieved the location error within 1m.

• Journal of the Korea Computer Graphics Society
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• v.26 no.1
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• pp.7-15
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• 2020

In the process of visualizing a point set representing a smooth manifold surface, global illumination techniques can be used to render a realistic scene with various effects of lighting. Thanks to the continuous demand for ray tracing and the development of graphics hardware, dedicated GPUs and programmable pipeline for ray tracing have been introduced in recent years. In this paper, real-time global illumination rendering is studied for a point-set model using ray-tracing GPUs. We apply the moving least-squares (MLS) method to approximate the point set to a smooth implicit surface and render it using global illumination by performing massive ray-intersection tests with the surface and generating shading effects at the intersection point. As a result, a complicated point-set scene consisting of more than 0.5M points can be generated in real-time.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.597-606
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• 2010

This paper describes a real-time camera tracking framework specifically designed to track a monocular camera in an AR workspace. Typically, the Kalman filter is often employed for the camera tracking. In general, however, tracking performances of conventional methods are seriously affected by unpredictable situations such as ambiguity in feature detection, occlusion of features and rapid camera shake. In this paper, a recursive Bayesian sampling framework which is also known as the particle filter is adopted for the camera pose estimation. In our system, the camera state is estimated on the basis of the Gaussian distribution without employing additional uncertainty model and sample weight computation. In addition, the camera state is directly computed based on new sample particles which are distributed according to the true posterior of system state. In order to verify the proposed system, we conduct several experiments for unstable situations in the desktop AR environments.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.5
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• pp.358-366
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• 2024

This paper proposes a method for the real-time camera tracking which detects and employs feature points located on a planar object in 3D space. The proposed approach operates in two stages. First, multiple feature points are detected in the 3D space, and then only those that exist on the planar object are selected. The camera's extrinsic parameters are then estimated using the projective geometry relationship between the feature points of the plane and the camera's image plane. The experiments are conducted in a typical indoor environment with regular lighting, without any special illumination setups. In contrast to conventional approaches, the proposed method can detect new feature points on the planar object in real-time and employ them for the camera tracking. This allows for continuous tracking even when the reference features for the camera pose initialization are not available. The experimental results show an average re-projection error of about 5 to 7 pixels, which is relatively small given the image resolution, and demonstrating that camera tracking is possible even in the absence of reference features within the image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2001.11b
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• pp.51-56
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• 2001

최근에 TV 방송에서 가상스튜디오나 가상캐릭터와 같은 가상현실(VR:Vinual Reality) 기술이 자주 사용되고 있으며, 증강현실(Ah: Augmented Reality) 기술에 대한 관심도 높아지고 있다. 본 논문에서는 증강현실 기술을 방송에 응용한 가상스크린 시스템에 대해 소개한다. 가상스크린 시스템은 움직이는 색상패턴 패널을 추적하여 실시간으로 그 위에 동영상을 합성하는 증강 영상 시스템이다. KBS 기술연구소에서는 가상스크린 시스템을 개발하고 'K-비전'이라 이름지었다. 이 시스템은 사용자가 들고 움직이는 패널에 동영상이나 그래픽 영상 등을 보여줄 수 있는데, 보여지는 모든 영상은 카메라의 움직임과 패널의 움직임에 따라 정확하게 입혀진다. 패널 추적을 위하여 블럽분석(blob analysis)이나 특징추적(feature tracking)과 같은 영상처리 기술을 이용한다. K-비전은 모든 타입의 카메라와 사용 가능하며, 특별한 부가장치가 필요하지 않다. 센서를 부착하지 않아도 되고, 캘리브레이션(calibration) 과정 또한 필요하지 않다. K-비전은 선거개표방송, 다큐멘터리, 오락 프로그램 등 생방송 프로그램에서 활용한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.335-337
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• 2016

리얼리티 예능 TV 프로그램이나 다큐멘터리, 스포츠 중계, 인터넷 개인 방송 등 다양한 방송 프로그램에서 기존의 촬영시스템과 다른 새로운 기기와 방법을 도입하고 있다. 특히 드론을 활용한 항공 촬영시스템으로 사람이나 지미짚 카메라로 촬영이 불가능했던 높은 구도에서 촬영하고, 액션 캠을 활용한 촬영시스템으로 사용자가 직접 휴대하거나 신체에 부착하여 역동적인 영상을 촬영하고 있다. 하지만 현재까지 개발 및 도입되고 있는 시스템들은 실내 촬영에 어려움과 영상 가장자리 왜곡 발생, 배터리 수명 문제로 장시간 촬영에 한계점이 있다. 이에 본 논문에서는 실시간으로 사용자를 검출하고 추적하면서 주변 환경과 사용자의 모습을 촬영하는 이동형 촬영 로봇 시스템을 제안하였다. 사용자의 제어 없이 실시간 촬영 및 저장 서비스를 제공하기 위해 로봇 스스로 카메라 영상을 통해 사용자를 검출, 위치 정보를 획득하고 이동하여 추적함으로써 근거리 영역을 유지한 상태로 새로운 기법과 구도에서 촬영하는 시스템을 구성하였다.

• Proceedings of the KAIS Fall Conference
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• 2010.11a
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• pp.39-42
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• 2010

산업의 발달과 경제 성장에 따른 차량의 증가는 교통 환경과 관련된 여러 문제를 유발하고 있다. 차량의 증가는 이러한 문제를 더욱 더 심각하게 만들고 있어 이를 해결하기 위한 방법의 모색이 필요하다. 차량의 번호판을 인식하는 것은 차량 정보를 인식하는데 중요하게 사용될 수 있고 효율적으로 교통문제를 개선할 수 있을 것이다. 본 논문은 실시간으로 촬영된 차량의 동영상 정보를 이용하여 자동차 번호판의 위치를 추적하는 기법을 제안하고, 동영상을 이용한 차량의 정보 수집이 어떠한 이점이 있는지와 향후 발전 가능성에 대한 설명을 포함한다.