• Journal of Information Technology Services
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• v.6 no.1
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• pp.127-140
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• 2007

Due to the development of information technologies and new businesses related to moving objects, the need for the storage and analysis of moving object data is increasing rapidly. Moving object data have a spatiotemporal nature which is different from typical business data. Therefore, different methods of data storage and analysis are required. This paper proposes a multidimensional data model and data visualization to analyze moving object data efficiently and effectively. We expect that decision makers can understand the movement pattern of moving objects more intuitively through the proposed implementation.

• The Journal of Society for e-Business Studies
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• v.2 no.2
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• pp.155-169
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• 1997

The CALS integrated database is a key information technology in which CALS implements an information sharing system to enable digital data transfers for technical and non-technical information in distributed and heterogeneous environments. Such heterogeneously distributed CALS information needs to be systematically incorporated so that it can provide a global data view for CALS users. In this paper, we investigated the technologies of CALS integrated database, and proposed a system prototype to implement an integrated data environment (IDE) utilizing distributed object environments CORBA (Common Object Request Broker Architecture).

• Journal of the Korea Society for Simulation
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• v.6 no.1
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• pp.61-69
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• 1997

In 3D computer graphics, fractal techniques have been applied to terrain models. Even though fractal models are convenient way to get the data of terrain models, it is not easy to gain the final results by manipulating the data of terrain model. However, by using the object oriented programming techniques, we could reduce the effort of programming job to find the final result. In this paper, a set of classes made by object oriented programming technique is presented. To show the results, the data of a terrain model were made by a fractal technique, namely, the midpoint displacement methods with square lattices of points.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.27-32
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• 1996

In target tracking area, the data association plays an important role and has been studied extensively. In this paper, after defining the data association as a constrained optimization, we introduce a new energy function and thereby an efficient realization of neural networks. As an application, this algorithm is used to detect object boundaries in IR images. The problem is that the IR image noisy, the shape of the object is variable, and the positions of the end points are not predictable. The performance of this algorithm is discussed with the experimental results.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.184-189
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• 2020

This paper is a study on data augmentation for small dataset by using deep learning. In case of training a deep learning model for recognition and classification of non-mainstream objects, there is a limit to obtaining a large amount of training data. Therefore, this paper proposes a data augmentation method using perspective transform and image synthesis. In addition, it is necessary to save the object area for all training data to detect the object area. Thus, we devised a way to augment the data and save object regions at the same time. To verify the performance of the augmented data using the proposed method, an experiment was conducted to compare classification accuracy with the augmented data by the traditional method, and transfer learning was used in model learning. As experimental results, the model trained using the proposed method showed higher accuracy than the model trained using the traditional method.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.893-903
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• 2022

Recently, computer vision (CV)-based safety monitoring (i.e., object detection) system has been widely researched in the construction industry. Sufficient and high-quality data collection is required to detect objects accurately. Such data collection is significant for detecting small objects or images from different camera angles. Although several previous studies proposed novel data augmentation and synthetic data generation approaches, it is still not thoroughly addressed (i.e., limited accuracy) in the dynamic construction work environment. In this study, we proposed a game engine-driven synthetic data generation model to enhance the accuracy of the CV-based object detection model, mainly targeting small objects. In the virtual 3D environment, we generated synthetic data to complement training images by altering the virtual camera angles. The main contribution of this paper is to confirm whether synthetic data generated in the game engine can improve the accuracy of the CV-based object detection model.

• Journal of Information Technology Applications and Management
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• v.10 no.1
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• pp.111-125
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• 2003

This paper proposes a product data model that can express and enforce integrity constraints on product structure during engineering changes (ECs). The model adopts and extends an active object-oriented database model in order to Integrate IC data and their integrity constraints. Tightly integrated with product structure, It will enable designers to maintain and exchange consistent EC data throughout the product life cycle. In order to properly support operations for ECs, the model provides the data, operations, and Event-Condition-Action rules for nested ECs and simultaneous EC applications to multiple options. in addition, the EC objects proposed In the model integrate the data and Integrity constraints into a unified repository. This repository enables designers to access all EC data and integrity constraints through the product structure and relationships between EC objects. This paper also describes a prototype product data management system based on the proposed model In order to demonstrate its effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.678-681
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• 2004

In this paper, efficient tracking of a moving object using optimal representative blocks is implemented by a mobile robot with a pan-tilt camera. The key idea comes from the fact that when the image size of moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by changing the size of representative blocks according to the object image size. Motion estimation using Edge Detection(ED) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. In this paper, the optimal representative block that can reduce a lot of data to be computed, is defined and optimized by changing the size of representative block according to the size of object in the image frame to improve the tracking performance. The proposed algorithm is verified experimentally by using a two degree-of-freedom active camera mounted on a mobile robot.

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.1-11
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• 1995

Object-oriented database systems represent the complex data model of real- world and manage the complex data. An object manager handles the manipulation and access of all objects in object-oriented database management systems. In this paper, we not only propose the design rules of an object manager interface(OMI) which is specified the calling function and the semantics of an object manager for object-oriented query processing, but also implement the OMI based on the rules. The OMI implemented supports the independently developing environment of query processing and object management modules, and can be applicable to various applications, and also provides the efficient access method to users.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.1
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• pp.27-35
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• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.