• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.387-400
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• 2021

The increase in number of streaming platforms and contents thereof, owing to an advancement of cloud environment, has triggered the rapid proliferation of illegally replicated contents as well as legal contents. This necessitates the development of technology capable of discriminating the copyright infringement of various contents. The Korea Copyright Protection Agency operates a video content demonstration system using AI, but it has limitations on distortions such as resolution changes. In this paper, we propose the powerful mechanism using skeleton, which is resistant against distorted video contents and capable of discriminating copyright infringement of platforms streaming illegal video contents. The proposed mechanism exploits the calculation of Hamming distance to the original video by converting collected data into binary ones for the efficient calculation. As a result of the experiment, the proposed mechanism have demonstrated the discrimination of illegally replicated video contents with an accuracy of 94.79% and average magnitude of 215KB.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.127-130
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• 2007

The increased availability of portable, low-cost, high resolution video devices has resulted in a rapid growth of the applications for video sequences. These video devices can be mounted in handhold unit, mobile unit and airborne platforms like maned or unmaned helicopter, plane, airship, etc. A core technique in use of video sequences is to align neighborhood video frames to each other or to reference images. For video sequences registration, we extracted interested points from aerial video sequences using Harris, $F{\square}rstner$, and KLT operators and implemented image matching using these points. As the result, we analysed image matching results for each operators and evaluated accuracy of aerial video registration.

• Asia-Pacific Journal of Business
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• v.12 no.2
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• pp.205-222
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• 2021

Purpose - Due to the Covic-19 pandemic, the perceived value of video conferencing platforms has been increased drastically. However, there is little guidance on how service providers can improve video conferencing platforms. The purpose of this study is to investigate the factors that influence the users' perceived value of video conferencing services based on the heuristic-systematic model and the value-based adoption model. Design/Methodology/Approach - In this paper, we theoretically explore the relationship of the antecedents of perceived value(credibility, expertise, attractiveness, economic feasibility, security, and interactivity) and its outcomes (perceived usefulness, perceived risk and perceived value). The outcomes of this research is a conceptualization of antecedents of perceived value supported by research hypothesis based on the existing literature. A total of 100 valid questionnaires were collected to empirically test the research model. Findings - The analysis results showed that credibility, economic feasibility, and interactivity positively influenced perceived usefulness. On the other hand, credibility, professionalism and interactivity negatively influenced perceived risk. Perceived usefulness positively affects perceived value and perceived risk has a negative effect on perceived value. The brand image as a moderating variable was found to decrease the effect of perceived risk on perceived value. Research Implications - The contribution of this study is significant for video conferencing providers as follows. First, a service provider can actively utilize influencers or referees with high credibility and expertise to maximize the perceived usefulness of users. Second, economic feasibility should be ensured in respect of users through various alliance discount strategies. Third, a video conferencing service company needs to build a positive brand image in order to increase users' perceived value.

• The Journal of Information Systems
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• v.27 no.4
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• pp.229-249
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• 2018

Purpose The purpose of this paper is to conduct exploratory comparative research on the determinants of successful crowdfunding projects, focusing on multiple crowdfunding platforms in Korea, U.S., and Japan. Design/methodology/approach This study collected data from three representative crowdfunding platforms: Wadiz (Korea), Kickstarter (U.S.), and Readyfor (Japan). Based on 1,906 crowdfunding projects from Wadiz, 3,864 projects from Kickstarter, and 3,060 projects from Readyfor, multiple regression models were applied. Findings Focusing on the crowdfunding projects which have overly achieved goal amount, the analysis results show that the number of comments, the number of Facebook likes and the number of backers have an positive impact on the performance of crowdfunding projects, while target amount has a negative impact. Comparatively, word counts of project description have an impact on funding performance in U.S. and Japan, while the number of images in project description affects funding performance in Korea and U.S. Meanwhile, video clips in project description has little impact on crowdfunding performance in all of the three funding platforms.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.273-277
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• 2021

As society gradually enters a virtual, non-face-to-face society, the use of online content is increasing as well. In particular, as smartphones are thoroughly established in our daily life, the platforms of webtoons, mobile broadcasting, and education are shifting from personal computers to smartphones. Recently, the development of the Over-The-Top media service (OTT service) enabled streaming services of various media contents through the internet and activation of IPTV. Therefore, the rapid increase of popularity of short-form content is a natural phenomenon with smartphone platforms with fast, improvised, and endless communication. Lately, TikTok became the favored platform with prosumers, defined as people who are both producers and consumers. In this study, I studied the experiential response of YouTube and TikTok users as representative examples of a short-form content platform developed after the 2000s, the flourishing years of digital content with a length of 30 seconds.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.288-294
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• 2022

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.81-93
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• 2023

The popularity of short-form video platforms like TikTok has increased recently. Short-form videos are significantly shorter than traditional videos, and viewers regularly switch between different types of content to watch. Therefore, a successful prefetching strategy is essential for this novel type of video. This study provides a resource-effective prefetching technique for streaming short-form videos. The suggested solution dynamically adjusts the quantity of prefetched video data based on user viewing habits and network traffic conditions. The results of the experiments demonstrate that, in comparison to baseline approaches, our method may reduce data waste by 21% to 83%, start-up latency by 50% to 99%, and the total time of Re-buffering by 90% to 99%.

• Journal of Web Engineering
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• v.20 no.8
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• pp.2413-2432
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• 2021

Recently, the demand for high-quality video content has rapidly been increasing, led by the development of network technology and the growth in video streaming platforms. In particular, displays with a high refresh rate, such as 120 Hz, have become popular. However, the visual quality is only enhanced if the video stream is produced at the same high frame rate. For the high quality, conventional videos with a low frame rate should be converted into a high frame rate in real time. This paper introduces a bidirectional intermediate flow estimation method for real-time video frame interpolation. A bidirectional intermediate optical flow is directly estimated to predict an accurate intermediate frame. For real-time processing, multiple frames are interpolated with a single intermediate optical flow and parts of the network are implemented in 16-bit floating-point precision. Perceptual loss is also applied to improve the cognitive performance of the interpolated frames. The experimental results showed a high prediction accuracy of 35.54 dB on the Vimeo90K triplet benchmark dataset. The interpolation speed of 84 fps was achieved for 480p resolution.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.1-9
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• 2022

The recent development of information and communication technology is also affecting audio/video systems used in industry. The audio/video device configuration system changes from analog to digital, and the network-based audio/video system control has the advantage of reducing costs in accordance with system operation. However, audio/video systems released on the market have limitations in that they can only control their own products or can only be performed on specific platforms (Windows, Mac, Linux). This paper is a study on a device (Network Audio Video Integrated Control: NAVICS) that can integrate and control multiple audio / video devices with different functions, and can control digitalized audio / video devices through network and serial communication. As a result of the study, it was confirmed that individual control and integrated control were possible through the protocol provided by each audio/video device by NAVICS, and that even non-experts could easily control the audio/video system. In the future, it is expected that network-based audio/video integrated control technology will become the technical standard for complex audio/video system control.