• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.15-28
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• 2019

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.183-188
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• 1998

This paper describes the concept of object-based coding for future broadcasting environments. Digital broadcasting uses the MPEG2 coding scheme which is regarded as a picture-based coding. An object-based coding scheme is a potential candidate for future broadcasting both for studio and distribution uses, and it offers a higher compression more flexible content handling. This paper also describes key technologies that we have been developing for the object-based coding, e.g., image analysis, object extraction and coding of objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1989-2011
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• 2019

Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.97.4-97
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• 2002

1. Introduction Pose estimation of a three dimensional object has been studied in robot vision area, and it is needed in a number of industrial applications such as process monitoring and control, assembly and PCB inspection. In this research, we propose a new pose estimation method based on principal axes analysis. Here, it is assumed that the locations of x-ray source and the image plane are predetermined and the object geometry is known. To this end, we define a dispersion matrix of an object, which is a discrete form of inertia matrix of the object. It can be determined here from a set of x-ray images, at least three images are required. Then, the pose information is obtained fro...

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.546-557
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• 2022

Recently, the demand to interpret image data with artificial intelligence in various fields is rapidly increasing. Object recognition and detection techniques using deep learning are mainly used, and video integration analysis to determine unstructured object recognition is a particularly important problem. In the case of natural disasters or social disasters, there is a limit to the object recognition structure alone because it has an unstructured shape. In this paper, we propose intelligent video integration analysis system that can recognize unstructured objects based on video turning point and object detection. We also introduce a method to apply and evaluate object recognition using virtual augmented images from 2D to 3D through GAN.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.1
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• pp.70-77
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• 2008

A pre-processing program based on the OOP(object-oriented programming) concept has been developed. The program consists of the input of a 2D or 3D flow problem to a CFD program by means of an user-friendly interface and the subsequent transformation of this input into a form suitable for the solver(PowerCFD) using unstructured cell-centered method. User-friendly GUI(graphic user interface) has been built on the base of MFC(Microsoft Foundation Class). The program is organized as modules by classes based on VTK(Visualization ToolKit)-library, and these classes are made to function through inheritance and cooperation which is an important and valuable concept of object-oriented programming. The major functions of this program are introduced and demonstrated, which include mesh generation, boundary settings, solver settings, generation of grid connectivity and geometric data etc.

• Journal of computational fluids engineering
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• v.9 no.2
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• pp.1-10
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• 2004

In the present study, a post-processing program is developed for 3D data visualization and analysis. Because the graphical user interface(GUI) of the program is based on Qt-library while all the graphic rendering is performed with OpenGL library, the program runs on not only MS Windows but also UNU and Linux systems without modifying source code. The structure of the program is designed according to the object-oriented programming(OOP) concept so that it has extensibility, reusability, and easiness compared to those by procedural programming. The program is organized as modules by classes, and these classes are made to function through inheritance and cooperation which is an important and valuable concept of object-oriented programming. The major functions realized so far which include mesh plot, contour plot, vector plot, streamline plot, and boundary plot are demonstrated and the relevant algorithms are described.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.399-408
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• 2020

The construction industry is suffering from aging workers, frequent accidents, as well as low productivity. With the rapid development of information technologies in recent years, automatic construction, especially automatic cranes, is regarded as a promising solution for the above problems and attracting more and more attention. However, in practice, limited by the complexity and dynamics of construction environment, manual inspection which is time-consuming and error-prone is still the only way to recognize the search object for the operation of crane. To solve this problem, an image-processing-based automated object recognition approach is proposed in this paper, which is a fusion of Convolutional-Neutral-Network (CNN)-based and traditional object detections. The search object is firstly extracted from the background by the trained Faster R-CNN. And then through a series of image processing including Canny, Hough and Endpoints clustering analysis, the vertices of the search object can be determined to locate it in 3D space uniquely. Finally, the features (e.g., centroid coordinate, size, and color) of the search object are extracted for further recognition. The approach presented in this paper was implemented in OpenCV, and the prototype was written in Microsoft Visual C++. This proposed approach shows great potential for the automatic operation of crane. Further researches and more extensive field experiments will follow in the future.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.35-42
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• 2013

Nowadays many tasks are performed using the Web. Accordingly, many web-based application systems with various and complicated functions are being requested. In order to develop such web-based application systems efficiently, object-oriented analysis and design methodology is used, and Java EE(Java Platform, Enterprise Edition) technologies are used for its implementation. The security issues have become increasingly important. For such reasons, Java EE provides mechanism related to security but it does not provide interconnections with object-oriented analysis and design methodology for developing web application system. Consequently, since the security method by Java EE mechanism is implemented at the last step only, it is difficult to apply constant security during the whole process of system development from the requirement analysis to implementation. Therefore, this paper suggests an object-oriented analysis and design methodology emphasized in the security for secure web application systems from the requirement analysis to implementation. The object-oriented analysis and design methodology adopts UMLsec, the modeling language with an emphasis on security for the requirement analysis and system analysis & design with regard to security. And for its implementation, RBAC (Role Based Access Control) of servlet from Java EE technologies is used. Also, the object-oriented analysis and design methodology for the secure web application is applied to online banking system in order to prove its effectiveness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.201-210
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• 2021

This paper introduces the futsal video analysis system consisting of an analysis program using object tracking technology and a web server that visualizes and provides analyzed data. In this paper, small and medium-sized organizations and amateur players are unable to provide game analysis services, so they propose a system that can solve this problem through this paper. Existing analytical systems use special devices or high-cost cameras, making them difficult for users to use. Thus, in this paper, a system is designed and developed to analyze the competitors' competitions and visualize the data using flat images only. Track an object and calculate the accumulated values to obtain the distance per pixel of the object and extract speed-related data and distance-based data based on it. Converts extracted data to graphs and images through a visualization library, making it convenient to use through web pages. Through this analysis system, we improve the problems of the existing analysis system and make data-based scientific and efficient analysis available.