• Title/Summary/Keyword: vision-based technology

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A Study on Conceptual Design of Local Community Knowledge Information System Based on Public Library 2.0 (Public Library 2.0 기반 지역 커뮤니티지식정보시스템 개념적 설계)

  • Park, Mi-Young;Seung, Hyon-Woo
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.21 no.1
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    • pp.193-209
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    • 2010
  • It is library service innovation that leading change as cultural leader in advance of original technology of knowledge information, sharing and forming a new system, creating a new knowledge in feedback relationship, and constructing a specified unique library in active interaction. The purpose of this study is to provide public library a new vision based on pubic library 2.0 service model through library service innovation in digital knowledge information age. This study aims to improvement community knowledge information system of conceptual design based on public library 2.0. It is summarized as follows: First, library 2.0 service model is proposed with library 2.0 definition, principle and essential factor through literal and e-journal search. Second, application case is searched centering around library 2.0 cooperating technology of blogs, wiki, instant messaging, podcast, social networking, flickr. Third, public library new vision is proposed by definition and principle of public library 2.0. This study is conceptual design for next generation public library and is needed follow research for system implementation and test.

Automated Construction Progress Management Using Computer Vision-based CNN Model and BIM (이미지 기반 기계 학습과 BIM을 활용한 자동화된 시공 진도 관리 - 합성곱 신경망 모델(CNN)과 실내측위기술, 4D BIM을 기반으로 -)

  • Rho, Juhee;Park, Moonseo;Lee, Hyun-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.21 no.5
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    • pp.11-19
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    • 2020
  • A daily progress monitoring and further schedule management of a construction project have a significant impact on the construction manager's decision making in schedule change and controlling field operation. However, a current site monitoring method highly relies on the manually recorded daily-log book by the person in charge of the work. For this reason, it is difficult to take a detached view and sometimes human error such as omission of contents may occur. In order to resolve these problems, previous researches have developed automated site monitoring method with the object recognition-based visualization or BIM data creation. Despite of the research results along with the related technology development, there are limitations in application targeting the practical construction projects due to the constraints in the experimental methods that assume the fixed equipment at a specific location. To overcome these limitations, some smart devices carried by the field workers can be employed as a medium for data creation. Specifically, the extracted information from the site picture by object recognition technology of CNN model, and positional information by GIPS are applied to update 4D BIM data. A standard CNN model is developed and BIM data modification experiments are conducted with the collected data to validate the research suggestion. Based on the experimental results, it is confirmed that the methods and performance are applicable to the construction site management and further it is expected to contribute speedy and precise data creation with the application of automated progress monitoring methods.

Error Correction Algorithm of Position-Coded Pattern for Hybrid Indoor Localization (위치패턴 기반 하이브리드 실내 측위를 위한 위치 인식 오류 보정 알고리즘)

  • Kim, Sanghoon;Lee, Seunggol;Kim, Yoo-Sung;Park, Jaehyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.2
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    • pp.119-124
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    • 2013
  • Recent increasing demand on the indoor localization requires more advanced and hybrid technology. This paper proposes an application of the hybrid indoor localization method based on a position-coded pattern that can be used with other existing indoor localization techniques such as vision, beacon, or landmark technique. To reduce the pattern-recognition error rate, the error detection and correction algorithm was applied based on Hamming code. The indoor localization experiments based on the proposed algorithm were performed by using a QCIF-grade CMOS sensor and a position-coded pattern with an area of $1.7{\times}1.7mm^2$. The experiments have shown that the position recognition error ratio was less than 0.9 % with 0.4 mm localization accuracy. The results suggest that the proposed method could be feasibly applied for the localization of the indoor mobile service robots.

Development of Augmented Reality Based 3D Model Interaction User-Interface for Supporting Ship Design Drawing Information (선박 설계도면 정보 제공을 위한 증강현실 기반의 3D 모델 상호작용 사용자 인터페이스 개발)

  • Oh, Youn-Jae;Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.12
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    • pp.1933-1940
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    • 2013
  • Recently, due to improvement of computer performance and development of information devices, technology of mobile augmented reality is proliferating rapidly. However, because most of contents are passive or limitary, user can not feel interest and immersion. This paper designs interaction user interface system of 2 dimensional drawing based on mobile augmented reality to make bi-directional communication between the real world and the virtual world possible by using the vision based augmented reality and the database system.

A Study of Shiitake Disease and Pest Image Analysis based on Deep Learning (딥러닝 기반 표고버섯 병해충 이미지 분석에 관한 연구)

  • Jo, KyeongHo;Jung, SeHoon;Sim, ChunBo
    • Journal of Korea Multimedia Society
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    • v.23 no.1
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    • pp.50-57
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    • 2020
  • The work that detection and elimination to disease and pest have important in agricultural field because it is directly related to the production of the crops, early detection and treatment of the disease insects. Image classification technology based on traditional computer vision have not been applied in part such as disease and pest because that is falling a accuracy to extraction and classification of feature. In this paper, we proposed model that determine to disease and pest of shiitake based on deep-CNN which have high image recognition performance than exist study. For performance evaluation, we compare evaluation with Alexnet to a proposed deep learning evaluation model. We were compared a proposed model with test data and extend test data. The result, we were confirmed that the proposed model had high performance than Alexnet which approximately 48% and 72% such as test data, approximately 62% and 81% such as extend test data.

Object Recognition of Robot Using 3D RFID System

  • Roh, Se-Gon;Park, Jin-Ho;Lee, Young-Hoon;Choi, Hyouk-Ryeol
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.62-67
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    • 2005
  • Object recognition in the field of robotics generally has depended on a computer vision system. Recently, RFID(Radio Frequency IDentification) technology has been suggested to support recognition and has been rapidly and widely applied. This paper introduces the more advanced RFID-based recognition. A novel tag named 3D tag, which facilitates the understanding of the object, was designed. The previous RFID-based system only detects the existence of the object, and therefore, the system should find the object and had to carry out a complex process such as pattern match to identify the object. 3D tag, however, not only detects the existence of the object as well as other tags, but also estimates the orientation and position of the object. These characteristics of 3D tag allows the robot to considerably reduce its dependence on other sensors required for object recognition the object. In this paper, we analyze the 3D tag's detection characteristic and the position and orientation estimation algorithm of the 3D tag-based RFID system.

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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.

An Indoor Pose Estimation System Based on Recognition of Circular Ring Patterns (원형 링 패턴 인식에 기반한 실내용 자세추정 시스템)

  • Kim, Heon-Hui;Ha, Yun-Su
    • Journal of Advanced Marine Engineering and Technology
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    • v.36 no.4
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    • pp.512-519
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    • 2012
  • This paper proposes a 3-D pose (positions and orientations) estimation system based on the recognition of circular ring patterns. To deal with monocular vision-based pose estimation problem, we specially design a circular ring pattern that has a simplicity merit in view of object recognition. A pose estimation procedure is described in detail, which utilizes the geometric transformation of a circular ring pattern in 2-D perspective projection space. The proposed method is evaluated through the analysis of accuracy and precision with respect to 3-D pose estimation of a quadrotor-type vehicle in 3-D space.

AI Processor Technology Trends (인공지능 프로세서 기술 동향)

  • Kwon, Youngsu
    • Electronics and Telecommunications Trends
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    • v.33 no.5
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    • pp.121-134
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    • 2018
  • The Von Neumann based architecture of the modern computer has dominated the computing industry for the past 50 years, sparking the digital revolution and propelling us into today's information age. Recent research focus and market trends have shown significant effort toward the advancement and application of artificial intelligence technologies. Although artificial intelligence has been studied for decades since the Turing machine was first introduced, the field has recently emerged into the spotlight thanks to remarkable milestones such as AlexNet-CNN and Alpha-Go, whose neural-network based deep learning methods have achieved a ground-breaking performance superior to existing recognition, classification, and decision algorithms. Unprecedented results in a wide variety of applications (drones, autonomous driving, robots, stock markets, computer vision, voice, and so on) have signaled the beginning of a golden age for artificial intelligence after 40 years of relative dormancy. Algorithmic research continues to progress at a breath-taking pace as evidenced by the rate of new neural networks being announced. However, traditional Von Neumann based architectures have proven to be inadequate in terms of computation power, and inherently inefficient in their processing of vastly parallel computations, which is a characteristic of deep neural networks. Consequently, global conglomerates such as Intel, Huawei, and Google, as well as large domestic corporations and fabless companies are developing dedicated semiconductor chips customized for artificial intelligence computations. The AI Processor Research Laboratory at ETRI is focusing on the research and development of super low-power AI processor chips. In this article, we present the current trends in computation platform, parallel processing, AI processor, and super-threaded AI processor research being conducted at ETRI.

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

  • Hur, Hyejung;Lee, Ju-Young
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.2
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    • pp.125-132
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    • 2014
  • In this paper, we present marker-less fingertip and brush tracking system with inexpensive web camera. Parallel computation using CUDA is applied to the tracking system. This tracking system can run on inexpensive environment such as a laptop or a desktop and support for real-time application. We also present realistic water-based sign pen drawing model and implementation. The realistic drawing application with our inexpensive real-time fingertip and brush tracking system shows us the art class of the future. The realistic drawing application, along with our inexpensive real-time fingertip and brush tracking system, would be utilized in test-bed for the future high-technology education environment.