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

검색결과 351건 처리시간 0.028초

컴퓨터시각증후군 예방을 위한 웹캠모니터의 실시간알림 시스템 (Real-time Notification System of Webcam Monitor for Preventing Computer Vision Syndrome)

  • 하상원;유도협;문미경
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2015년도 춘계학술대회
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    • pp.754-755
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    • 2015
  • 컴퓨터의 보급과 인터넷의 대중화로 컴퓨터를 통한 작업은 물론 여가 시간이나 가정에서도 컴퓨터를 이용하는 시간이 늘고 있다. 이에 따라 컴퓨터를 오래 사용하여 생기는 질환인 컴퓨터시각증후군 (Computer Vision Syndrome: CVS)도 증가하는 추세이다. CVS 증후군으로 인한 안구건조증은 컴퓨터나 TV 등 모니터를 집중하여 주시하면 자기도 모르게 눈 깜빡임이 줄어들면서 눈물이 빠르게 증발되어 생기는 질환이다. 이를 예방하기 위해서는 눈의 건조를 막기 위해 눈을 자주 깜빡거려줘야 하며, 모니터와 눈은 40cm이상 거리를 유지해야 한다. 본 논문에서는 모니터의 웹캠을 이용하여 사용자의 모니터 근접거리, 사용자의 눈 깜빡임 정도를 실시간으로 감시한 후 적절한 알림을 주는 웹 캠모니터의 실시간 알림시스템의 개발 내용에 대해 기술한다.

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컴퓨터 비전 기술을 활용한 관객의 움직임과 상호작용이 가능한 실시간 파티클 아트 (Real-time Interactive Particle-art with Human Motion Based on Computer Vision Techniques)

  • 조익현;박거태;정순기
    • 한국멀티미디어학회논문지
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    • 제21권1호
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    • pp.51-60
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    • 2018
  • We present a real-time interactive particle-art with human motion based on computer vision techniques. We used computer vision techniques to reduce the number of equipments that required for media art appreciations. We analyze pros and cons of various computer vision methods that can adapted to interactive digital media art. In our system, background subtraction is applied to search an audience. The audience image is changed into particles with grid cells. Optical flow is used to detect the motion of the audience and create particle effects. Also we define a virtual button for interaction. This paper introduces a series of computer vision modules to build the interactive digital media art contents which can be easily configurated with a camera sensor.

비전 센서를 사용하는 실시간 물류 파악 시스템 구현 (Implementation of Real-time Logistics Identification System using Vision Sensors)

  • 김동휘;박민혁;박성재;박정규
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2022년도 추계학술대회
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    • pp.172-174
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    • 2022
  • 국내에서 물류를 처리하는 회사에서는 다양한 형태의 제품을 입출고 처리하고 있다. 다양한 형태의 제품을 처리하기 위해서 수작업으로 분류 업부를 수행하고 있다. 본 논문에서는 적은 인력으로 고효율을 내기 위해 비전 센서를 사용하는 실시간 QR코드 탐지 방법을 제안한다. 제한하는 시스템은 비전 센서를 사용하여 물류의 QR코드 인식을 실시간으로 처리가 가능하다. 제안하는 시스템은 물류의 단인 QR 코드 인식이 아닌 다중 인식을 통해서 다량의 QR 코드를 빠르게 파악할 수 있다. 연구에서는 시스템을 실제 구현하여 검증을 진행하여 비전 센터를 통해서 이미지에서 다중 QR 인식을 확인하였다.

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A Platform-Based SoC Design for Real-Time Stereo Vision

  • Yi, Jong-Su;Park, Jae-Hwa;Kim, Jun-Seong
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제12권2호
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    • pp.212-218
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    • 2012
  • A stereo vision is able to build three-dimensional maps of its environment. It can provide much more complete information than a 2D image based vision but has to process, at least, that much more data. In the past decade, real-time stereo has become a reality. Some solutions are based on reconfigurable hardware and others rely on specialized hardware. However, they are designed for their own specific applications and are difficult to extend their functionalities. This paper describes a vision system based on a System on a Chip (SoC) platform. A real-time stereo image correlator is implemented using Sum of Absolute Difference (SAD) algorithm and is integrated into the vision system using AMBA bus protocol. Since the system is designed on a pre-verified platform it can be easily extended in its functionality increasing design productivity. Simulation results show that the vision system is suitable for various real-time applications.

A Computer Vision-Based Banknote Recognition System for the Blind with an Accuracy of 98% on Smartphone Videos

  • Sanchez, Gustavo Adrian Ruiz
    • 한국컴퓨터정보학회논문지
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    • 제24권6호
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    • pp.67-72
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    • 2019
  • This paper proposes a computer vision-based banknote recognition system intended to assist the blind. This system is robust and fast in recognizing banknotes on videos recorded with a smartphone on real-life scenarios. To reduce the computation time and enable a robust recognition in cluttered environments, this study segments the banknote candidate area from the background utilizing a technique called Pixel-Based Adaptive Segmenter (PBAS). The Speeded-Up Robust Features (SURF) interest point detector is used, and SURF feature vectors are computed only when sufficient interest points are found. The proposed algorithm achieves a recognition accuracy of 98%, a 100% true recognition rate and a 0% false recognition rate. Although Korean banknotes are used as a working example, the proposed system can be applied to recognize other countries' banknotes.

객체 탐지 과업에서의 트랜스포머 기반 모델의 특장점 분석 연구 (A Survey on Vision Transformers for Object Detection Task)

  • 하정민;이현종;엄정민;이재구
    • 대한임베디드공학회논문지
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    • 제17권6호
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    • pp.319-327
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    • 2022
  • Transformers are the most famous deep learning models that has achieved great success in natural language processing and also showed good performance on computer vision. In this survey, we categorized transformer-based models for computer vision, particularly object detection tasks and perform comprehensive comparative experiments to understand the characteristics of each model. Next, we evaluated the models subdivided into standard transformer, with key point attention, and adding attention with coordinates by performance comparison in terms of object detection accuracy and real-time performance. For performance comparison, we used two metrics: frame per second (FPS) and mean average precision (mAP). Finally, we confirmed the trends and relationships related to the detection and real-time performance of objects in several transformer models using various experiments.

Real-time geometry identification of moving ships by computer vision techniques in bridge area

  • Li, Shunlong;Guo, Yapeng;Xu, Yang;Li, Zhonglong
    • Smart Structures and Systems
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    • 제23권4호
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    • pp.359-371
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    • 2019
  • As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

전자태그와 컴퓨터 비전 시스템을 이용한 생산 공정 감시와 재일정계획 (Manufacturing process monitoring and Rescheduling using RFID and Computer vision system)

  • 공재현;한만철;박진우
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2005년도 춘계학술대회 논문집
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    • pp.153-156
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    • 2005
  • Real-time monitoring and controlling manufacturing process is important because of the unexpected events. When unexpected event like mechanical trouble occurs, prior plan becomes unacceptable and a new schedule must be generated though manufacturing schedule is already decided for order. Regenerating the whole schedule, however, spends much time and cost. Thus automated system which monitors and controls manufacturing process is required. In this paper, we present a system which uses radio-frequency identification and computer vision system. The system collect real-time information about manufacturing conditions and generates new schedule quickly with those information.

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Real-Time Pipe Fault Detection System Using Computer Vision

  • Kim Hyoung-Seok;Lee Byung-Ryong
    • International Journal of Precision Engineering and Manufacturing
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    • 제7권1호
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    • pp.30-34
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    • 2006
  • Recently, there has been an increasing demand for computer-vision-based inspection and/or measurement system as a part of factory automation equipment. In general, it is almost impossible to check the fault of all parts, coming from part-feeding system, with only manual inspection because of time limitation. Therefore, most of manual inspection is applied to specific samples, not all coming parts, and manual inspection neither guarantee consistent measuring accuracy nor decrease working time. Thus, in order to improve the measuring speed and accuracy of the inspection, a computer-aided measuring and analysis method is highly needed. In this paper, a computer-vision-based pipe inspection system is proposed, where the front and side-view profiles of three different kinds of pipes, coming from a forming line, are acquired by computer vision. And the edge detection is processed by using Laplace operator. To reduce the vision processing time, modified Hough transform is used with clustering method for straight line detection. And the center points and diameters of inner and outer circle are found to determine eccentricity of the parts. Also, an inspection system has been built so that the data and images of faulted parts are stored as files and transferred to the server.