• Title/Summary/Keyword: Real-Time Computer Vision

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Real Time Eye and Gaze Tracking (트래킹 Gaze와 실시간 Eye)

  • Min Jin-Kyoung;Cho Hyeon-Seob
    • Proceedings of the KAIS Fall Conference
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    • 2004.11a
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    • pp.234-239
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    • 2004
  • This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process fur each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

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Design and Implementation of Depth Image Based Real-Time Human Detection

  • Lee, SangJun;Nguyen, Duc Dung;Jeon, Jae Wook
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.14 no.2
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    • pp.212-226
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    • 2014
  • This paper presents the design and implementation of a pipelined architecture and a method for real-time human detection using depth image from a Time-of-Flight (ToF) camera. In the proposed method, we use Euclidean Distance Transform (EDT) in order to extract human body location, and we then use the 1D, 2D scanning window in order to extract human joint location. The EDT-based human extraction method is robust against noise. In addition, the 1D, 2D scanning window helps extracting human joint locations easily from a distance image. The proposed method is designed using Verilog HDL (Hardware Description Language) as the dedicated hardware architecture based on pipeline architecture. We implement the dedicated hardware architecture on a Xilinx Virtex6 LX750 Field Programmable Gate Arrays (FPGA). The FPGA implementation can run 80 MHz of maximum operating frequency and show over 60fps of processing performance in the QVGA ($320{\times}240$) resolution depth image.

A method of generating virtual shadow dataset of buildings for the shadow detection and removal

  • Kim, Kangjik;Chun, Junchul
    • Journal of Internet Computing and Services
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    • v.21 no.5
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    • pp.49-56
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    • 2020
  • Detecting shadows in images and restoring or removing them was a very challenging task in computer vision. Traditional researches used color information, edges, and thresholds to detect shadows, but there were errors such as not considering the penumbra area of shadow or even detecting a black area that is not a shadow. Deep learning has been successful in various fields of computer vision, and research on applying deep learning has started in the field of shadow detection and removal. However, it was very difficult and time-consuming to collect data for network learning, and there were many limited conditions for shooting. In particular, it was more difficult to obtain shadow data from buildings and satellite images, which hindered the progress of the research. In this paper, we propose a method for generating shadow data from buildings and satellites using Unity3D. In the virtual Unity space, 3D objects existing in the real world were placed, and shadows were generated using lights effects to shoot. Through this, it is possible to get all three types of images (shadow-free, shadow image, shadow mask) necessary for shadow detection and removal when training deep learning networks. The method proposed in this paper contributes to helping the progress of the research by providing big data in the field of building or satellite shadow detection and removal research, which is difficult for learning deep learning networks due to the absence of data. And this can be a suboptimal method. We believe that we have contributed in that we can apply virtual data to test deep learning networks before applying real data.

QUANTIFICATION OF COW′S BODY PARAMETERS USING COMPUTER VISION

  • Lee, D. W.;Kim, H. T.;Kim, Y. S.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2000.11b
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    • pp.344-353
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    • 2000
  • Recent mechatronics technology is the most appropriate high technology in the agricultural application to save repetitious labor. Cow's body parameters were measured by traditional several measurer. Image processing technology was used to measure automatically their parameters to reduce lots of labor and time. The parameters were measured form a small model cow, which is easily measured, instead to a real cow. The image processing system designed and built for this project was composed of a Pentium PC, and TV frame card two cameras which were located on side and top of model cow. 11 parameters of cow's body were measured and the error between real data and the data by image processing was less than 10%. Based on the results of this research the parameters of a real cow could be measured in the future.

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Optimal algorithm of FOV for solder joint inspection using neural network (신경회로망을 이용한 납땜 검사 FOV의 최적화 알고리즘)

  • 오제휘;차영엽
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1549-1552
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    • 1997
  • In this paper, a optimal algorithm that can produce the FOV is proposed in terms of using the Kohonen's Self-Organizing Map(KSOM). A FOV, that stands for "Field Of View", means maximum area where a camera could be wholly seen and influences the total time of inspection of vision system. Therefore, we draw algorithm with a KSOM which aims to map an input space of N-dimensions into a one-or two-dimensional lattice of output layer neurons in order to optimize the number and location of FOV, instead of former sequentila method. Then, we show demonstratin through computer simulation using the real PCB data. PCB data.

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A Study of the B/STUD Inspection System Using the Vision System (비전을 이용한 B/STUD 검사 시스템에 관한 연구)

  • 장영훈;한창수
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.1120-1123
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    • 1995
  • In this paper, an automatic B/STUD inspection system has been developed using the computer aided vision system. Index Table has been used to get the rapid measurement and multi-camera has been used to get the high resolution in mechanical system. Camera calibration was suggested to perform the reliable Inspection. Image processing and data analysis algorithms for B/STUD inspection system has been investigated and were performed quickly with high accuracy. As a result, Inspection system of a B/STUD can be measured with a high resolution in real time.

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The Technology of Measurement System for Contact Wire Uplift (전차선 압상 검측을 위한 시스템 기술)

  • Park, Young;Cho, Hyeon-Young;Kim, Hyung-Chul;Kwon, Sam-Young;Kim, In-Chol;Choi, Won-Seok
    • Proceedings of the KSR Conference
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    • 2009.05a
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    • pp.900-904
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    • 2009
  • The measurement of contact wire uplift in electric railway is one of the most test method to accept the maximum permitted speed of new vehicles or pantographs. The contact wire uplift can be measured for shot periods when pantograph is running in monitoring station. This paper describes the development of two different methods for contact uplift measurement using vision-based system and wireless online monitoring system. Our vision-based system employs a high-speed CMOS (Complementary Metal Oxide Semiconductor) camera with gigabit ethernet LAN. The development of a real-time remote monitoring system that acquires data from any kind of sensor to be transmitted by wireless communication from overhead line and structure at 25 kV to a computer in catenary system. The proposed two kind of different measurement systems to evaluation for dynamic uplift of overhead contact wire shows promising on-field applications for high speed train such as Korea Tilting Train (TTX) and Korea Train eXpress (KTX).

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A Video Traffic Flow Detection System Based on Machine Vision

  • Wang, Xin-Xin;Zhao, Xiao-Ming;Shen, Yu
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1218-1230
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    • 2019
  • This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

Hardware Architecture for Entropy Filter Implementation (엔트로피 필터 구현에 대한 Hardware Architecture)

  • Sim, Hwi-Bo;Kang, Bong-Soon
    • Journal of IKEEE
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    • v.26 no.2
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    • pp.226-231
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    • 2022
  • The concept of information entropy has been widely applied in various fields. Recently, in the field of image processing, many technologies applying the concept of information entropy have been developed. As the importance and demand of computer vision technologies increase in modern industry, real-time processing must be possible in order for image processing technologies to be efficiently applied to modern industries. Extracting the entropy value of an image is difficult to process in real-time due to the complexity of computation in software, and a hardware structure of an image entropy filter capable of real-time processing has never been proposed. In this paper, we propose for the first time a hardware structure of a histogram-based entropy filter that can be processed in real time using a barrel shifter. The proposed hardware was designed using Verilog HDL, and Xilinx's xczu7ev-2ffvc1156 was set as the target device and FPGA was implemented. As a result of logic synthesis using the Xilinx Vivado program, it has a maximum operating frequency of 750.751 MHz in a 4K UHD high-resolution environment, and it processes more than 30 images per second and satisfies the real-time processing standard.

Design and Implementation of a Concentration-based Review Support Tool for Real-time Online Class Participants (실시간 온라인 수업 수강자들의 집중력 기반 복습 지원 도구의 설계 및 구현)

  • Tae-Hwan Kim;Dae-Soo Cho;Seung-Min Park
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.3
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    • pp.521-526
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    • 2023
  • Due to the recent pandemic, most educational systems are being conducted through online classes. Unlike face-to-face classes, it is even more difficult for learners to maintain concentration, and evaluating the learners' attitude toward the class is also challenging. In this paper, we proposed a real-time concentration-based review support system for learners in real-time video lectures that can be used in online classes. This system measured the learner's face, pupils, and user activity in real-time using the equipment used in the existing video system, and delivers real-time concentration measurement values to the instructor in various forms. At the same time, if the concentration measurement value falls below a certain level, the system alerted the learner and records the timestamp of the lecture. By using this system, instructors can evaluate the learners' participation in the class in real-time and help to improve their class abilities.