• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.454-460
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• 2000

To retrieve complex data such as images, the content-based retrieval method rather than keyword based method is required. In this paper, we implemented a content-based image retrieval system which retrieves object of user query effectively using invariant moments which have invariant properties about linear transformation like position transition, rotation and scaling. To extract the shape feature of objects in an image, we propose a labeling algorithm that extracts objects from an image and apply invariant moments to each object. Hashing method is also applied to reduce a retrieval time and index images effectively. The experimental results demonstrate the high retrieval efficiency i.e precision 85%, recall 23%. Consequently, our retrieval system shows better performance than the conventional system that cannot express the shale of objects exactly.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.617-632
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• 2004

Video Data includes moving objects which change spatial positions as time goes by. In this paper, we propose a new modeling method for a moving object contained in the video data. In order to effectively retrieve moving objects, the proposed modeling method represents the spatial position and the size of a moving object. It also represents the visual features and the trajectory by considering direction, distance and speed or moving objects as time goes by. Therefore, It allows various types of retrieval such as visual feature based similarity retrieval, distance based similarity retrieval and trajectory based similarity retrieval and their mixed type of weighted retrieval.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.88-96
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• 2015

The recent increase in the production of 3D contents allowed viewers to experience various 3D contents. However, some of the viewers did not experience 3D depth well. Several researches were done in past to measure viewers' 3D depth perception, but these researches were done with certain limitations. In this paper, we measured viewers' 3D depth perception and recovery rate in relation with the changes in binocular disparities, saturation, and brightness values after subjects' watching 2D/3D contents. The results showed that when viewers watched the 3D content with positive binocular disparities for 42 minutes, viewers felt that the object seemed to have moved further forward than it was before; with 3D content with negative binocular disparities, viewers felt that the object seemed to be moved backwards. We found that the locational differences of the object in positive disparities were greater than those in the negative binocular disparities. The recovery rate was computed by comparing two measured values of before and after watching 3D contents for 30 minutes. On average, after 30-minute break, viewers showed roughly 50 % of recovery rate.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.54-60
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• 2021

AR (Augmented Reality) is a technology that provides virtual content to the real world and provides additional information to objects in real-time through 3D content. In the past, a high-performance device was required to experience AR, but it was possible to implement AR more easily by improving mobile performance and mounting various sensors such as ToF (Time-of-Flight). Also, the importance of mobile augmented reality is growing with the commercialization of high-speed wireless Internet such as 5G. Thus, this paper proposes a system that can provide AR services via GNN (Graph Neural Network) using cameras and sensors on mobile devices. ToF of mobile devices is used to capture depth maps. A 3D point cloud was created using RGB images to distinguish specific colors of objects. Point clouds created with RGB images and Depth Map perform downsampling for smooth communication between mobile and server. Point clouds sent to the server are used for 3D object detection. The detection process determines the class of objects and uses one point in the 3D bounding box as an anchor point. AR contents are provided through app and web through class and anchor of the detected object.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2381-2398
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• 2024

The construction of virtual indoor spaces is crucial for the development of metaverses, virtual production, and other 3D content domains. Traditional methods for creating these spaces are often cost-prohibitive and labor-intensive. To address these challenges, we present a pipeline for generating digital twins of real indoor environments from RGB-D camera-scanned data. Our pipeline synergizes space structure estimation, 3D object detection, and the inpainting of missing areas, utilizing deep learning technologies to automate the creation process. Specifically, we apply deep learning models for object recognition and area inpainting, significantly enhancing the accuracy and efficiency of virtual space construction. Our approach minimizes manual labor and reduces costs, paving the way for the creation of metaverse spaces that closely mimic real-world environments. Experimental results demonstrate the effectiveness of our deep learning applications in overcoming traditional obstacles in digital twin creation, offering high-fidelity digital replicas of indoor spaces. This advancement opens for immersive and realistic virtual content creation, showcasing the potential of deep learning in the field of virtual space construction.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.165-168
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• 2013

Image distortions, such as quantization errors, can have a severe negative impact on the performance of computer vision algorithms, and, more specifically, on object detection algorithms. State-of-the-art implementations of the JPEG-2000 image coder commonly allocate the available bits to minimize the Mean-Squared-Error (MSE) distortion between the original image and the resulting compressed image. However, considering that some state-of-the-art object detection methods use the gradient information as the main image feature, an improved object detection performance is expected for JPEG-2000 image coders that allocate the available bits to minimize the distortions on the gradient content. Accordingly, in this work, the Gradient Mean-Squared-Error (GMSE) based JPEG-2000 coder presents an improved object detection performance over the MSE based JPEG-2000 image coder when the object of interest is located at the same spatial location of the image regions with the strongest gradients and also for high bit-rates. For low bit-rates (e.g. 0.07bpp), the GMSE based JPEG-2000 image coder becomes overly selective in choosing the gradients to preserve, and, as a result, there is a greater chance of mismatch between the spatial locations of the gradients that the coder is trying to preserve and the spatial locations of the objects of interest.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4120-4132
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• 2017

In this research, we implement a deformable object simulation system using OpenGL's shader language, GLSL4.3. Deformable object simulation is implemented by using volumetric mass-spring system suitable for real-time simulation among the methods of deformable object simulation. The compute shader in GLSL 4.3 which helps to access the GPU resources, is used to parallelize the operations of existing deformable object simulation systems. The proposed system is implemented using a compute shader for parallel processing and it includes a bounding box-based collision detection solution. In general, the collision detection is one of severe computing bottlenecks in simulation of multiple deformable objects. In order to validate an efficiency of the system, we performed the experiments using the 3D volumetric objects. We compared the performance of multiple deformable object simulations between CPU and GPU to analyze the effectiveness of parallel processing using GLSL. Moreover, we measured the computation time of bounding box-based collision detection to show that collision detection can be processed in real-time. The experiments using 3D volumetric models with 10K faces showed the GPU-based parallel simulation improves performance by 98% over the CPU-based simulation, and the overall steps including collision detection and rendering could be processed in real-time frame rate of 218.11 FPS.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.111-118
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• 2012

The purpose of this study is to classify the epistemological critique between philosophy and architecture. Although there are various interpretations and criticism about the architecture, the fundamental critique of architecture is difficult. It is necessary to approach by the philosophic paradigm rather than architectural one. Therefore the procedure and method of study is to define the epistemology within philosophy and architecture, and present the classification viewpoint and the architecture case. The conclusions of this study based on purpose and process are as follows : The First, the philosophic epistemology is to mean the unity of subjective and objective. And the epistemological viewpoint of architectural philosophy is to define the construction's universality. The second, the architectural philosophy is a kind of the philosophy of art, and It is associated with the basis of aesthetics. Thus, the category of architectural philosophy like the aesthetics is classified with function directivity and form directivity, content directivity. The Last, epistemological critiques between philosophy and architecture are as follows ; 1) subject-object-integrated recognition critique (function directivity), 2) object-oriented recognition critique (form directivity), 3) subject-oriented recognition critique (content directivity).

• The Research Journal of the Costume Culture
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• v.8 no.4
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• pp.537-548
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• 2000

This paper focuses on development of a fashion design education course that will foster the talent and aesthetic consciousness of fashion design student. The writer reached the content of the designing ideas to practical applications as the defined scope of fashion design education. For designing idea in practical application : matching ideas, contrasting ideas, formative combinations and revisionism were used. For design ideas, the ideas developed by 飯塚弘子, 万江入重子, 香川達子 were used in revision. To detail the content of design education, fashion magazines, portfolios, photographs and related fashion design educational materials were used. 1. Matching ideas : it proposes such identical expression into costume by making a research of developing material, application form and color extraction from design sources. 2. Contrasting ideas : it proposes such opposite expression into costume by making a research of opposite to image, form, position and purpose from some object. 3. Formative combinations : it proposes such new expression into costume by combining a detail of costume with the other object. 4. Revisionism : it proposes such modified expression into costume by making a research of deletion, change, addition and conversion in costume.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1377-1389
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• 2016

This paper presents a target model update scheme for the mean-shift tracking with background weighted histogram. In the scheme, the target candidate histogram is corrected by considering the back-projection weight of each pixel in the kernel after the best target candidate in the current frame image is chosen. In each frame, the target model is updated by the weighted average of the current target model and the corrected target candidate. We compared our target model update scheme with the previous ones by applying several test sequences. The experimental results showed that the object tracking accuracy was greatly improved by using the proposed scheme.