• 제목/요약/키워드: object model

검색결과 4,043건 처리시간 0.171초

A Multimedia Query Language for Object-Oriented Multimedia Databases (객체 지향 멀티미디어 데이타베이스를 위한 멀티미디어 질의어)

  • 노윤묵;이석호;김규철
    • Journal of the Korean Institute of Telematics and Electronics B
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    • 제32B권5호
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    • pp.671-682
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    • 1995
  • In this paper, we propose a multimedia query language MQL which defines and manipulates multimedia data as integration of monomedia data in time and space. The MQL is designed for a multimedia data model, called the object-relationship model, and based on the multimedia object calculus which formally describes operations on multimedia data. The SQL- like syntax for class definition and object manipulation, such as retrieval, insert, update, and delete, is defined. We show how the MQL can represent the user queries using composite temporal-spatial class structures and various relationships, such as equivalence and sequence.

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Object Motion Detection and Tracking Based on Human Perception System (인간의 지각적인 시스템을 기반으로 한 연속된 영상 내에서의 움직임 영역 결정 및 추적)

  • 정미영;최석림
    • Proceedings of the IEEK Conference
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2120-2123
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    • 2003
  • This paper presents the moving object detection and tracking algorithm using edge information base on human perceptual system The human visual system recognizes shapes and objects easily and rapidly. It's believed that perceptual organization plays on important role in human perception. It presents edge model(GCS) base on extracted feature by perceptual organization principal and extract edge information by definition of the edge model. Through such human perception system I have introduced the technique in which the computers would recognize the moving object from the edge information just like humans would recognize the moving object precisely.

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A Fuzzy Object Data Model (퍼지 객체 데이터 모델에 관한 고찰)

  • 이진호;이전영
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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    • pp.129-132
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    • 1996
  • In this paper, we suggest a framework to represent the fuzziness in knowledge base as a perspective of the object-oriented paradigm. We divide the knowledge base in two parts. One is the object-base that stores the fuzzy propositions and the explanatory databases. The other is the rule-base that manages the rules between the fuzzy propositions. As the first step, we have to develop a new fuzzy object model that gives an easy way to represent the fuzzy propositions, that is, the fuzzy knowledge in the real world.

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Object Recognition Using Planar Surface Segmentation and Stereo Vision

  • Kim, Do-Wan;Kim, Sung-Il;Won, Sang-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1920-1925
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    • 2004
  • This paper describes a new method for 3D object recognition which used surface segment-based stereo vision. The position and orientation of an objects is identified accurately enabling a robot to pick up, even though the objects are multiple and partially occluded. The stereo vision is used to get the 3D information as 3D sensing, and CAD model with its post processing is used for building models. Matching is initially performed using the model and object features, and calculate roughly the object's position and orientation. Though the fine adjustment step, the accuracy of the position and orientation are improved.

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Classification of Ontology Integration and Ontology-based Semantic Integration of PLM Object (온톨로지 통합 분류와 온톨로지 기반의 PLM Object 의미적 통합)

  • Kwak, Jung-Ae;Yong, Hwan-Seung;Choi, Sang-Su
    • Korean Journal of Computational Design and Engineering
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    • 제13권3호
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    • pp.163-174
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    • 2008
  • In this paper, for integrating of data on car parts we model information of parts that PDM system manages. Ontology of car parts applies existing ontology mapping research to integrate into car ontology. We propose a method for semantic integration of PLM object of MEMPHIS based on the integrated ontology. Through our method, we introduce C# ontology model to apply existing C# applications with ontology. We also classify ontology integration into three through examples and explain them. While semantically integrating PLM objects based on the integrated ontology, we explain the need for change of PLM object type and describe the process of change for PLM object type by examples.

Extending Object-Oriented Models with Scoping Constructs (객체지향 모델에서 사용범위 기능 도입에 관한 연구)

  • 권기항;김지승
    • Journal of Korea Multimedia Society
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    • 제2권2호
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    • pp.195-199
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    • 1999
  • While object-oriented models are effective in achieving sharing and code reusability, they unfortunately lack a mechanism for giving scope to objects. We propose an object-oriented model in which each object can be given a scope, i.e., an object becomes available only when it is needed. Thus, the set of currently available objects is dynamically changing and only the needed set of objects is maintained in this model. We illustrate the usefulness of this model through some examples.

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Octree model based fast three-dimensional object recognition (Octree 모델에 근거한 고속 3차원 물체 인식)

  • 이영재;박영태
    • Journal of the Korean Institute of Telematics and Electronics C
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    • 제34C권9호
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    • pp.84-101
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    • 1997
  • Inferring and recognizing 3D objects form a 2D occuluded image has been an important research area of computer vision. The octree model, a hierarchical volume description of 3D objects, may be utilized to generate projected images from arbitrary viewing directions, thereby providing an efficient means of the data base for 3D object recognition. We present a fast algorithm of finding the 4 pairs of feature points to estimate the viewing direction. The method is based on matching the object contour to the reference occuluded shapes of 49 viewing directions. The initially best matched viewing direction is calibrated by searching for the 4 pairs of feature points between the input image and the image projected along the estimated viewing direction. Then the input shape is recognized by matching to the projectd shape. The computational complexity of the proposed method is shown to be O(n$^{2}$) in the worst case, and that of the simple combinatorial method is O(m$^{4}$.n$^{4}$) where m and n denote the number of feature points of the 3D model object and the 2D object respectively.

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Collaborative Object-Oriented Analysis for Production Control Systems

  • Kim, Chang-Ouk
    • Journal of Korean Society of Industrial and Systems Engineering
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    • 제23권56호
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    • pp.19-34
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    • 2000
  • Impact of business process re-engineering requires the fundamental rethinking of how information systems are analyzed and designed. It is no longer sufficient to establish a monolithic system for fixed business environments. Information systems must be adaptive in nature. This demand is also applied in production domain. Enabling concept for the adaptive information system is reusability. This paper presents a new object-oriented analysis process for creating such reusable software components in production domain, especially for production planning and scheduling. Our process called MeCOMA is based on three meta-models: physical object meta-model, data object meta-model, and activity object meta-model. After the three meta-models are extended independently for a given production system, they are collaboratively integrated on the basis of integration pattern. The main advantages of MeCOMA are (1) to reduce software development time and (2) to consistently build reusable production software components.

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Quantity Measurement by CAFFE Model and Distance and Width Measurement by Stereo Vision (CAFFE 모델을 이용한 수량 측정 및 스테레오 비전을 이용한 거리 및 너비측정)

  • Kim, Won-Seob;Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • 제14권4호
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    • pp.679-684
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    • 2019
  • We propose a method to measure the number of specific species of class using CAFFE model and a method to measure length and width of object using stereo vision. To obtain the width of an object, the location coordinates of objects appearing on the left and right sensor is compared and the distance from the sensor to the object is obtained. Then the length of the object in the image by using the distance and the approximate value of the actual length of the object is calculated.

Development of a Deep Learning Algorithm for Small Object Detection in Real-Time (실시간 기반 매우 작은 객체 탐지를 위한 딥러닝 알고리즘 개발)

  • Wooseong Yeo;Meeyoung Park
    • Journal of the Korean Society of Industry Convergence
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    • 제27권4_2호
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    • pp.1001-1007
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    • 2024
  • Recent deep learning algorithms for object detection in real-time play a crucial role in various applications such as autonomous driving, traffic monitoring, health care, and water quality monitoring. The size of small objects, in particular, significantly impacts the accuracy of detection models. However, data containing small objects can lead to underfitting issues in models. Therefore, this study developed a deep learning model capable of quickly detecting small objects to provide more accurate predictions. The RE-SOD (Residual block based Small Object Detector) developed in this research enhances the detection performance for small objects by using RGB separation preprocessing and residual blocks. The model achieved an accuracy of 1.0 in image classification and an mAP50-95 score of 0.944 in object detection. The performance of this model was validated by comparing it with real-time detection models such as YOLOv5, YOLOv7, and YOLOv8.