• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.99-112
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• 1994

An important modelling requirement for multimedia systems is the representation of temporal constraints among several different media that ordinarily arise in multimedia application. The multimedia system which integrates various types of data is required to express voice, image, text and graphic data with simultaneousness or an arbitrary time intervals. The purpose of this study is to analyze the temporal reationships and synchronization among several different kinds of medium. Moreover, it proposes a Multimedia Display-Time Composition Model (MDTC Model) which guarantees a representation of any kind of temporal synchronization among more than two kinds of medium. The proposed model is applied to a company advertizing system. Finally, a multimedia authoring tool based on the MDTC Model is implemented.

• Korea Multimedia Society
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• v.4 no.3
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• pp.22-33
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• 2000

• Journal of Korean Library and Information Science Society
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• v.36 no.4
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• pp.365-387
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• 2005

This paper provides a state-of-the-art on multimedia metadata. After a brief introduction to multimedia metadata, the paper described and analyzed the main metadata initiatives. The results show that these initiatives described the bibliographic elements rather than metadata for contents representation. On the other hand, MPEG-7 covers a rich and detail aspects for representing the complete and consistent multimedia content.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1404-1413
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• 2014

The purpose of this study is to figure out the effects of multimedia fairy tale and narrative fairy tale lectures on children's language expression ability and drawing representation ability. To achieve this, this study was conducted from March to April, 2011 with 50 five-year-old children(25 children in the experimental group and 25 children in the comparative group) in K and S kindergartens at D metropolitan city. The results were as follows. First, the score of children's language expression ability was higher in the multimedia fairy tale lecture group than in the narrative fairy-tale lecture group. Second, the score of children's drawing representation ability was higher in the multimedia fairy tale lecture group than in the narrative fairy-tale lecture group. As for findings stated above, educational activities with multimedia were important in early childhood education. Consequently, children can better understand stories through multimedia fairy tales and various language activities, and improve their language expression ability and drawing representation ability through the process of exploring and drawing heroes in fairy tales. However, they have more need of educational activities, which are complementary to the merit of narrative fairy tale, than educational activities for only multimedia fairy tale lecture.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.173-180
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• 2018

This paper proposes a method to improve the performance of face recognition via super-resolution method using sparse representation and deep learning from low-resolution facial images. Recently, there have been many researches on ultra-high-resolution images using deep learning techniques, but studies are still under way in real-time face recognition. In this paper, we combine the sparse representation and deep learning to generate super-resolution images to improve the performance of face recognition. We have also improved the processing speed by designing in parallel structure when applying sparse representation. Finally, experimental results show that the proposed method is superior to conventional methods on various images.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.240-248
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• 2014

We present a robust speaker identification algorithm that uses novel features based on soft bag-of-word representation and a simple Naive Bayes classifier. The bag-of-words (BoW) based histogram feature descriptor is typically constructed by summarizing and identifying representative prototypes from low-level spectral features extracted from training data. In this paper, we define a generalization of the standard BoW. In particular, we define three types of BoW that are based on crisp voting, fuzzy memberships, and possibilistic memberships. We analyze our mapping with three common classifiers: Naive Bayes classifier (NB); K-nearest neighbor classifier (KNN); and support vector machines (SVM). The proposed algorithms are evaluated using large datasets that simulate medical crises. We show that the proposed soft bag-of-words feature representation approach achieves a significant improvement when compared to the state-of-art methods.

• Journal of The Korean Association of Information Education
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• v.5 no.2
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• pp.185-196
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• 2001

Elementary school students feel more difficult the mathematical word problems than the numberical formula. I think that this reason isn't the ability of mathematical calculation but the problems representation. It is demanded exactly understanding about the requirements of problem for improving ability of the mathematical word problem representation. It is necessary that we take multimedia data and communication for this, because web advances multimedia materialization and promotes mutual communication, then it gives us with the most environment for word problem representation learning. According to, this thesis is designed web-based system to improve ability of the mathematical word problem representation, applied the sixth grade it experimentally.

• Archives of design research
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• v.15 no.1
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• pp.113-122
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• 2002

This thesis is focused on online education and proposes a guideline for selecting teaming theories and multimedia representation without difficulty. On the first, consideration of learning theories and analysis of multimedia properties are made, and from these results guidelines are formed. Then they are applied to each 6 types of CAI. Objectivism and constructivism could be used for the basic framework of CAI. The former is suitable for reed, sequential, structural, and passive learning style and the latter is suitable for selectable, unstructural, active, self-controled, learning style. And the quideline for selecting multimedia representation is made out of the properties of media, learners(cognitive model, proficiency, acceptance), and teaming contents. On the basis of guideline obtaining from the previous process, I suggest mosts suitable conditions for each 6 types of CAI available today. Those conditions are consist of learning theories, media selection, levels of learners, and categories and properties of teaming contents.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.758-768
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• 2017

In this paper, we present a novel method to extract face representation based on multi-resolution spatial pyramid. In our method, a face is subdivided into increasingly finer sub-regions (local regions) and represented at multiple levels of histogram representations. To cope with misaligned problem, patch-based local descriptor extraction has been also developed in a novel way. To preserve multiple levels of detail in local characteristics and also encode holistic spatial configuration, histograms from all levels of spatial pyramid are integrated by using dimensionality reduction and feature combination, leading to our spatial-pyramid face feature representation. We incorporate our proposed face features into general face recognition pipeline and achieve state-of-the-art results on challenging face recognition problems.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.262-268
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• 2017

Intelligent video surveillance systems have been developed to monitor global areas and find specific target objects using a large-scale database. However, person re-identification presents some challenges, such as pose change and occlusions. To solve the problems, this paper presents an improved person re-identification method using sparse representation and saliency-based dictionary construction. The proposed method consists of three parts: i) feature description based on salient colors and textures for dictionary elements, ii) orthogonal atom selection using cosine similarity to deal with pose and viewpoint change, and iii) measurement of reconstruction error to rank the gallery corresponding a probe object. The proposed method provides good performance, since robust descriptors used as a dictionary atom are generated by weighting some salient features, and dictionary atoms are selected by reducing excessive redundancy causing low accuracy. Therefore, the proposed method can be applied in a large scale-database surveillance system to search for a specific object.