• Title/Summary/Keyword: Content Object

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A Research about e-Learning Contents Management System using Version Management Techniques and LCMS (버전관리 기법과 LCMS의 연동을 통한 e-Learning학습 콘텐츠 관리 시스템에 관한 연구)

  • Kim, Nam-Ho;Park, Young-B.
    • 한국정보교육학회:학술대회논문집
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    • 2008.01a
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    • pp.251-256
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    • 2008
  • e-Learning은 시 공간의 제약 없이 교수자와 학습자간의 교육이 이루어진다는 장점이 있는 반면, 다양한 학습자의 요구를 만족시킬 만큼 충분한 학습 콘텐츠의 제작이 어렵다는 단점이 있다. 이러한 단점을 해결하기 위해 ADL(Advanced Distributed Learning)의 SCORM(Sharable Content Object Reference Modeling)의 표준에 따라 e-Learning의 학습 콘텐츠를 학습객체(Learning Object)로 제작하고, 이를 SCORM의 표준을 지원하는 LCMS(Learning Content Management System)를 이용하여 관리하려는 연구가 진행되고 있다. LCMS를 이용할 경우 학습 콘텐츠의 제사용성을 높이므로 학습 콘텐츠의 제작 및 관리가 무척 용이해진다는 장점이 있는 반면 탈맥락화된 학습 콘텐츠를 제작하기는 매우 어렵다는 단점을 가진다. 본 연구에서는 이러한 문제점을 해결하기 위해 버전관리 기법을 이용한 탈맥락화된 학습 콘텐츠에 대한 제작이 용이한 시스템을 연구했다.

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Visual Modeling and Content-based Processing for Video Data Storage and Delivery

  • Hwang Jae-Jeong;Cho Sang-Gyu
    • Journal of information and communication convergence engineering
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    • v.3 no.1
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    • pp.56-61
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    • 2005
  • In this paper, we present a video rate control scheme for storage and delivery in which the time-varying viewing interests are controlled by human gaze. To track the gaze, the pupil's movement is detected using the three-step process : detecting face region, eye region, and pupil point. To control bit rates, the quantization parameter (QP) is changed by considering the static parameters, the video object priority derived from the pupil tracking, the target PSNR, and the weighted distortion value of the coder. As results, we achieved human interfaced visual model and corresponding region-of-interest rate control system.

A Study on Marker-based Detection Method of Object Position using Perspective Projection

  • Park, Minjoo;Jang, Kyung-Sik
    • Journal of information and communication convergence engineering
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    • v.20 no.1
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    • pp.65-72
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    • 2022
  • With the mark of the fourth industrial revolution, the smart factory is evolving into a new future manufacturing plant. As a human-machine-interactive tool, augmented reality (AR) helps workers acquire the proficiency needed in smart factories. The valuable data displayed on the AR device must be delivered intuitively to users. Current AR applications used in smart factories lack user movement calibration, and visual fiducial markers for position correction are detected only nearby. This paper demonstrates a marker-based object detection using perspective projection to adjust augmented content while maintaining the user's original perspective with displacement. A new angle, location, and scaling values for the AR content can be calculated by comparing equivalent marker positions in two images. Two experiments were conducted to verify the implementation of the algorithm and its practicality in the smart factory. The markers were well-detected in both experiments, and the applicability in smart factories was verified by presenting appropriate displacement values for AR contents according to various movements.

Uncertain Region Based User-Assisted Segmentation Technique for Object-Based Video Editing System (객체기반 비디오 편집 시스템을 위한 불확실 영역기반 사용자 지원 비디오 객체 분할 기법)

  • Yu Hong-Yeon;Hong Sung-Hoon
    • Journal of Korea Multimedia Society
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    • v.9 no.5
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    • pp.529-541
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    • 2006
  • In this paper, we propose a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the selected objects are continuously separated from the un selected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable and efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on this result, we have developed objects based video editing system with several convenient editing functions.

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Labeling-BMA Algorithms for VOP of MPEG-4 (MPEG-4에 사용되는 동영상 객체면의 구성을 위한 레이블링과 블록 정합 방법)

  • 최정화;한수영;임제탁
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.1091-1094
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    • 1999
  • In this paper, we propose new algorithms to construct video object planes(VOP’s) for MPEG-4. VOP’s allow the new video standard MPEG-4 to enable content-based funtionalities. A comprehensive review summarizes some of the most important VOP’s generation techniques that have been proposed. The proposed algorithm use segmentation technique as labeling and motion estimation as three-step search algorithm(TSS). It is improved by a labeling technique that distinguishes background and object from a frame.

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Statistical Investigation on Class Mutation Operators

  • Ma, Yu-Seung;Kwon, Yong-Rae;Kim, Sang-Woon
    • ETRI Journal
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    • v.31 no.2
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    • pp.140-150
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    • 2009
  • Although mutation testing is potentially powerful, it is a computationally expensive testing method. To investigate how we can reduce the cost of object-oriented mutation testing, we have conducted empirical studies on class mutation operators. We applied class mutation operators to 866 classes contained in six open-source programs. An analysis of the number and the distribution of class mutants generated and preliminary data on the effectiveness of some operators are provided. Our study shows that the overall number of class mutants is smaller than for traditional mutants, which offers the possibility that class mutation can be made practically affordable.

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Adaptive Image Content-Based Retrieval Techniques for Multiple Queries (다중 질의를 위한 적응적 영상 내용 기반 검색 기법)

  • Hong Jong-Sun;Kang Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.73-80
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    • 2005
  • Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

A Comparison Study on Data Caching Policies of CCN (콘텐츠 중심 네트워킹의 데이터 캐시 정책 비교 연구)

  • Kim, Dae-Youb
    • Journal of Digital Convergence
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    • v.15 no.2
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    • pp.327-334
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    • 2017
  • For enhancing network efficiency, various applications/services like CDN and P2P try to utilize content which have previously been cached somewhere. Content-centric networking (CCN) also utilizes data caching functionality. However, dislike CDN/P2P, CCN implements such a function on network nodes. Then, any intermediated nodes can directly respond to request messages for cached data. Hence, it is essential which content is cached as well as which nodes cache transmitted content. Basically, CCN propose for every nodes on the path from the content publisher of transmitted object to a requester to cache the object. However, such an approach is inefficient considering the utilization of cached objects as well as the storage overhead of each node. Hence, various caching mechanisms are proposed to enhance the storage efficiency of a node. In this paper, we analyze the performance of such mechanisms and compare the characteristics of such mechanisms. Also, we analyze content utilization patterns and apply such pattern to caching mechanisms to analyze the practicalism of the caching mechanisms.

Stencil-based 3D facial relief creation from RGBD images for 3D printing

  • Jung, Soonchul;Choi, Yoon-Seok;Kim, Jin-Seo
    • ETRI Journal
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    • v.42 no.2
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    • pp.272-281
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    • 2020
  • Three-dimensional (3D) selfie services, one of the major 3D printing services, print 3D models of an individual's face via scanning. However, most of these services require expensive full-color supporting 3D printers. The high cost of such printers poses a challenge in launching a variety of 3D printing application services. This paper presents a stencil-based 3D facial relief creation method employing a low-cost RGBD sensor and a 3D printer. Stencil-based 3D facial relief is an artwork in which some parts are holes, similar to that in a stencil, and other parts stand out, as in a relief. The proposed method creates a new type of relief by combining the existing stencil techniques and relief techniques. As a result, the 3D printed product resembles a two-colored object rather than a one-colored object even when a monochrome 3D printer is used. Unlike existing personalization-based 3D printing services, the proposed method enables the printing and delivery of products to customers in a short period of time. Experimental results reveal that, compared to existing 3D selfie products printed by monochrome 3D printers, our products have a higher degree of similarity and are more profitable.

Human Detection using Real-virtual Augmented Dataset

  • Jongmin, Lee;Yongwan, Kim;Jinsung, Choi;Ki-Hong, Kim;Daehwan, Kim
    • Journal of information and communication convergence engineering
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    • v.21 no.1
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    • pp.98-102
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    • 2023
  • This paper presents a study on how augmenting semi-synthetic image data improves the performance of human detection algorithms. In the field of object detection, securing a high-quality data set plays the most important role in training deep learning algorithms. Recently, the acquisition of real image data has become time consuming and expensive; therefore, research using synthesized data has been conducted. Synthetic data haves the advantage of being able to generate a vast amount of data and accurately label it. However, the utility of synthetic data in human detection has not yet been demonstrated. Therefore, we use You Only Look Once (YOLO), the object detection algorithm most commonly used, to experimentally analyze the effect of synthetic data augmentation on human detection performance. As a result of training YOLO using the Penn-Fudan dataset, it was shown that the YOLO network model trained on a dataset augmented with synthetic data provided high-performance results in terms of the Precision-Recall Curve and F1-Confidence Curve.