• 제목/요약/키워드: Real-Time Computer Vision

검색결과 361건 처리시간 0.03초

색상패턴 추적을 이용한 실시간 증강영상 시스템 (A Real-time Augmented Video System using Chroma-Pattern Tracking)

  • 박성춘;남승진;오주현;박창섭
    • 방송공학회논문지
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    • 제7권1호
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    • pp.2-9
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    • 2002
  • 최근에 TV 방송에서 가상스튜디오나 가상캐릭터와 같은 가상현실(VR: Virtual Reality) 기술이 자주 사용되고 있으며 증강현실 (AR: 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 증강영상 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 블럽 분석(blob analysis)이나 특징 추적(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 선거개표 방송. 다큐멘터리, 오락 프로그램 등 생방송 프로그램에서 활용한다.

실시간 영상에서 피부색상 정보와 Haar-Like Feature를 이용한 얼굴 검출 및 추적 (Face Detection and Tracking using Skin Color Information and Haar-Like Features in Real-Time Video)

  • 김동현;임재현;김대희;김태경;백준기
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2009년도 학술대회
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    • pp.146-149
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    • 2009
  • 실시간 영상에서 사람의 얼굴 검출은 얼굴 인식분야에 있어서 주요한 관심 분야 중의 하나이다. 본 논문에서는 실시간 입력되는 영상에서 피부 색상과 Haar-like feature를 이용한 얼굴 검출 및 추적 알고리듬을 제안한다. 제안된 알고리듬은 컬러 색 공간에서 피부색상과 특징점을 가지고 얼굴 영역 및 추적하였다. 실험 결과 실시간 영상에 대해 조명 변화 및 가림 현상에서 강건한 추적 결과를 얻을 수 있었다.

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실시간 배경갱신 및 이를 이용한 객체추적 (Real time Background Estimation and Object Tracking)

  • 이완주
    • 정보학연구
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    • 제10권4호
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    • pp.27-39
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    • 2007
  • Object tracking in a real time environment is one of challenging subjects in computer vision area during past couple of years. This paper proposes a method of object detection and tracking using adaptive background estimation in real time environment. To obtain a stable and adaptive background, we combine 3-frame differential method and running average single gaussian background model. Using this background model, we can successfully detect moving objects while minimizing false moving objects caused by noise. In the tracking phase, we propose a matching criteria where the weight of position and inner brightness distribution can be controlled by the size of objects. Also, we adopt a Kalman Filter to overcome the occlusion of tracked objects. By experiments, we can successfully detect and track objects in real time environment.

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실시간 운영체제를 탑재한 원격 제어 로봇 시스템 (Remote Controlled Robot System using Real-Time Operating System)

  • 이태희;조상
    • 제어로봇시스템학회논문지
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    • 제10권8호
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    • pp.689-695
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    • 2004
  • This paper presents a robot system that combines computer network and an autonomous mobile robot where RTOS is installed. We propose a wireless communication protocol, and also implement it on the RTOS of the robot system. Main controller of the robot processes the control program as a task type in the real-time operating system. Peripheral devices are driven by the device driver functions with the dependency of the hardware. Because the client and server program was implemented to support the multi-platforms by Java SDK and Java JMF, it is easy to analyze programs, maintain system, and correct the errors in the system. End-user can control a robot with a vision showing remote sight over the Internet in real time, and the robot is moved keeping away from the obstacles by itself and command of the server received from end-user at the local client.

Current Trend and Direction of Deep Learning Method to Railroad Defect Detection and Inspection

  • Han, Seokmin
    • International Journal of Internet, Broadcasting and Communication
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    • 제14권3호
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    • pp.149-154
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    • 2022
  • In recent years, the application of deep learning method to computer vision has shown to achieve great performances. Thus, many research projects have also applied deep learning technology to railroad defect detection. In this paper, we have reviewed the researches that applied computer vision based deep learning method to railroad defect detection and inspection, and have discussed the current trend and the direction of those researches. Many research projects were targeted to operate automatically without visual inspection of human and to work in real-time. Therefore, methods to speed up the computation were also investigated. The reduction of the number of learning parameters was considered important to improve computation efficiency. In addition to computation speed issue, the problem of annotation was also discussed in some research projects. To alleviate the problem of time consuming annotation, some kinds of automatic segmentation of the railroad defect or self-supervised methods have been suggested.

Real-Time Object Tracking and Segmentation Using Adaptive Color Snake Model

  • Seo Kap-Ho;Shin Jin-Ho;Kim Won;Lee Ju-Jang
    • International Journal of Control, Automation, and Systems
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    • 제4권2호
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    • pp.236-246
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    • 2006
  • Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks such as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. In this paper, the development of new snake model called 'adaptive color snake model (ACSM)' for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. For robust tracking, the condensation algorithm was adopted to control the parameters of ACSM. The effectiveness of the ACSM is verified by appropriate simulations and experiments.

자율 주차 시스템을 위한 실시간 차량 추출 알고리즘 (A Real-time Vehicle Localization Algorithm for Autonomous Parking System)

  • 한종우;최영규
    • 반도체디스플레이기술학회지
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    • 제10권2호
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    • pp.31-38
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    • 2011
  • This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

향상된 트래킹 시스템과 실시간 수성 사인펜을 위한 사실적 드로잉 (Improved Tracking System and Realistic Drawing for Real-Time Water-Based Sign Pen)

  • 허혜정;이주영
    • 한국컴퓨터정보학회논문지
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    • 제19권2호
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    • pp.125-132
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    • 2014
  • 본 논문에서는 저가의 웹 카메라를 사용하여 마커 없이 손끝과 붓을 트래킹 하는 시스템을 제시한다. 트래킹 시스템은 CUDA를 사용하여 병렬처리를 적용했다. 이 트래킹 시스템은 노트북이나 데스크탑과 같은 환경에서 수행이 가능하고, 실시간 애플리케이션에 사용 가능한 성능을 가진다. 또한 본 논문에서는 사적인 수성 사인펜 드로잉 모델을 제시하고 구현된 결과를 보여준다. 제안하는 시스템은 손끝과 붓을 트래킹 하는 저가의 실시간 트래킹 시스템으로 사실적 드로잉 애플리케이션과 연동하여 미래 최첨단 교육 환경 구축의 테스트베드로의 활용을 기대한다.

Fast Random-Forest-Based Human Pose Estimation Using a Multi-scale and Cascade Approach

  • Chang, Ju Yong;Nam, Seung Woo
    • ETRI Journal
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    • 제35권6호
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    • pp.949-959
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    • 2013
  • Since the recent launch of Microsoft Xbox Kinect, research on 3D human pose estimation has attracted a lot of attention in the computer vision community. Kinect shows impressive estimation accuracy and real-time performance on massive graphics processing unit hardware. In this paper, we focus on further reducing the computation complexity of the existing state-of-the-art method to make the real-time 3D human pose estimation functionality applicable to devices with lower computing power. As a result, we propose two simple approaches to speed up the random-forest-based human pose estimation method. In the original algorithm, the random forest classifier is applied to all pixels of the segmented human depth image. We first use a multi-scale approach to reduce the number of such calculations. Second, the complexity of the random forest classification itself is decreased by the proposed cascade approach. Experiment results for real data show that our method is effective and works in real time (30 fps) without any parallelization efforts.

A Runge-Kutta scheme for smart control mechanism with computer-vision robotics

  • ZY Chen;Huakun Wu;Yahui Meng;Timothy Chen
    • Smart Structures and Systems
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    • 제34권2호
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    • pp.117-127
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    • 2024
  • A novel approach that the smart control of robotics can be realized by a fuzzy controller and an appropriate Runge-Kutta scheme in this paper. A recently proposed integral inequality is selected based on the free weight matrix, and the less conservative stability criterion is given in the form of linear matrix inequalities (LMIs). We demonstrate that this target information obtained through image processing is subjected to smart control with computer-vision robotic to Arduino, and the infrared beacon was utilized for the operation of practical illustrations. A fuzzy controller derived with a fuzzy Runge-Kutta type functions is injected into the system and then the system is stabilized asymptotically. In this study, a fuzzy controller and a fuzzy observer are proposed via the parallel distributed compensation technique to stabilize the system. This paper achieves the goal of real-time following of three vehicles and there are many areas where improvements were made. Finally, each information is transmitted to Arduino via I2C to follow the self-propelled vehicle. The proposed calculation is approved in reproductions and ongoing smart control tests.