• 한국공작기계학회논문집
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• 제16권1호
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• pp.9-18
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• 2007

There have been continuous efforts for automation of joint tracking system. This automation process is mainly used to do in root pass of gas metal arc welding in the field of heavy industry and shipbuilding etc. For automation, it is important using of vision sensor. Welding robot with vision sensor is used for weld seam tracking on welding fabrication. Recently, it is used to on post-weld inspection for weld quality evaluation. For real time seam tracking, it is very important role in vision process technique. Vision process is included in filtering and thinning, segmentation processing, feature extraction and recognition. In this paper, it has shown performance comparison results of seam tracking for real time root pass on gas metal arc welding. It can be concluded better segment splitting method than iterative averaging technique in the performance results of seam tracking.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1491-1494
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• 2002

The paper introduces a novel system of two hands real-time tracking based on the unrestricted hand skin segmentation by multi color systems. After corer-based segmentation and pre-processing operation, a label set of regions is created to locate the two hands automatically. By the normalization, template matching is used to find out the left or right hand. An improved fast self-adaptive tracking algorithm is applied and Canny filter is used for hand detection.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 춘계학술발표대회
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• pp.436-439
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• 2012

The work is to the control the desktop Computers based on hand gesture recognition. This paper is worked en real time tracking and recognizes the hand gesture for controlling the slides based on hand direction such as right and left using a real time camera.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권3호
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• pp.162-170
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• 2014

Appearance-based subspace models such as eigenfaces have been widely recognized as one of the most successful approaches to face recognition and tracking. The success of eigenfaces mainly has its origins in the benefits offered by principal component analysis (PCA), the representational power of the underlying generative process for high-dimensional noisy facial image data. The sparse extension of PCA (SPCA) has recently received significant attention in the research community. SPCA functions by imposing sparseness constraints on the eigenvectors, a technique that has been shown to yield more robust solutions in many applications. However, when SPCA is applied to facial images, the time and space complexity of PCA learning becomes a critical issue (e.g., real-time tracking). In this paper, we propose a very fast and scalable greedy forward selection algorithm for SPCA. Unlike a recent semidefinite program-relaxation method that suffers from complex optimization, our approach can process several thousands of data dimensions in reasonable time with little accuracy loss. The effectiveness of our proposed method was demonstrated on real-world face recognition and tracking datasets.

• 전자공학회논문지CI
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• 제41권4호
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• pp.85-94
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• 2004

실시간 영상에서 객체 추적은 수년간 컴퓨터 비전 및 여러 실용적 응용 분야에서 관심을 가지는 주제 중 하나이다 하지만 배경영상의 잡음을 객체로 인식하는 오류로 인하여 추출하고자 하는 객체를 찾지 못하는 경우가 있다. 본 논문에서는 실시간 영상에서 적응적 배경영상을 이용하여 객체를 추출하고 추적하는 방법을 제안한다. 입력되는 영상에서 배경영역의 잡음을 제거하고 조명에 강인한 객체 추출을 위하여 객체영역이 아닌 배경영역 부분을 실시간으로 갱신함으로써 적응적 배경영상을 생성한다. 그리고 배경영상과 카메라로부터 입력되는 입력영상과의 차를 이용하여 객체를 추출한다. 추출된 객체의 내부점을 이용하여 최소사각영역을 설정하고, 이를 통해 객체를 추적한다. 아울러 제안방법의 성능에 대한 실험결과를 기존 추적알고리즘과 비교, 분석하여 평가한다.

• 한국컴퓨터정보학회논문지
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• 제27권1호
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• pp.1-8
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• 2022

본 논문에서는 실시간 객체 탐지(Real-time Object Detection)가 가능한 YOLOv4 모델과 DeepSORT 알고리즘을 활용한 객체 추적(Object Tracking) 기술을 활용하여 CCTV 영상 이미지 기반의 화재 탐지 시스템을 제안한다. 화재 탐지 모델은 10800장의 학습용 데이터로부터 학습되었으며 1000장의 별도 테스트 셋을 통해 검증되었다. 이후 DeepSORT 알고리즘을 통해 탐지된 화재 영역을 추적하여 단일 이미지 내의 화재 탐지율과 영상 내에서의 화재 탐지 유지성능을 증가시켰다. 영상 내의 한 프레임 혹은 단일 이미지에 대한 화재 탐지 속도는 장당 0.1초 이내로 실시간 탐지가 가능함을 확인하였으며 본 논문의 AI 화재 탐지 시스템은 기존의 화재 사고 탐지 시스템 보다 안정적이고 빠른 성능을 지니고 있어 화재현장에 적용 시 화재를 조기 발견하여 빠른 대처 및 발화단계에서의 진화가 가능할 것으로 예상된다.

• Smart Structures and Systems
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• 제14권6호
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• pp.1197-1220
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• 2014

Accurate actuator tracking is critical to achieve reliable real-time hybrid simulation results for earthquake engineering research. The frequency-domain evaluation approach provides an innovative way for more quantitative post-simulation evaluation of actuator tracking errors compared with existing time domain based techniques. Utilizing the Fast Fourier Transform the approach analyzes the actuator error in terms of amplitude and phrase errors. Existing application of the approach requires using the complete length of the experimental data. To improve the computational efficiency, two techniques including data decimation and frequency decimation are analyzed to reduce the amount of data involved in the frequency-domain evaluation. The presented study aims to enhance the computational efficiency of the approach in order to utilize it for future on-line actuator tracking evaluation. Both computational simulation and laboratory experimental results are analyzed and recommendations on the two decimation factors are provided based on the findings from this study.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.421-431
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• 2022

The purpose of this research is to determine the point of fixation of the driver during the process of driving. Based on the results of this research, the driving instructor can make a judgement on what the trainee stare on the most. Traffic accidents have become a serious concern in modern society. Especially, the traffic accidents among unskilled and elderly drivers are at issue. A driver should put attention on the vehicles around, traffic signs, passersby, passengers, road situation and its dashboard. An eye-tracking-based application was developed to analyze the driver's gaze behavior. It is a prototype for real-time eye tracking for monitoring the point of interest of drivers in driving practice. In this study, the driver's attention was measured by capturing the movement of the eyes in real road driving conditions using these tools. As a result, dwelling duration time, entry time and the average of fixation of the eye gaze are leading parameters that could help us prove the idea of this study.

• 정보처리학회논문지B
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• 제9B권6호
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• pp.707-714
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• 2002

본 연구에서는 능동카메라에서 취득된 영상에서 이동물체를 효율적으로 추적하기위한 실시간 Hausdorff 정합 알고리즘을 제안하였다. 알고리즘은 이동물체의 윤곽선영상을모델로 사용하고, Hausdorff 거리를 모델과 영상사이의 동일성 판별을 위한 평가함수로 사용하였으며, 실시간 처리를 위하여 Hausdorff 거리를 고속으로 계산하기 위한 등가변환방법과 기존 탐색알고리즘의 탐색회수를 줄이고 성능을 개선할 수 있는 반 교차정합기법을 제안하였다. 실험영상에 대한 모의실험 결과 제안한 알고리즘은 이동물체의 위치를 정확히 탐색할 수 있으며, 실시간 처리가 가능하도록 처리시간을 단축시킬 수 있음을 입증하였다.

• 한국IT서비스학회지
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• 제6권3호
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• pp.241-249
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• 2007

This paper describes a real-time face tracking system using effective detector and Kalman filter. In the proposed system, an image is separated into a background and an object using a real-time updated face color for effective face detection. The face features are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted using Principal Component Analysis (PCA), and interpreted principal components are used for Support Vector Machine (SVM) that classifies the faces and non-faces. The moving face is traced with Kalman filter, which uses the static information of the detected faces and the dynamic information of changes between previous and current frames. The proposed system sets up an initial skin color and updates a region of a skin color through a moving skin color in a real time. It is possible to remove a background which has a similar color with a skin through updating a skin color in a real time. Also, as reducing a potential-face region using a skin color, the performance is increased up to 50% when comparing to the case of extracting features from a whole region.