• Journal of Digital Convergence
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• v.18 no.9
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• pp.391-402
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• 2020

In today's era of media convergence, users can watch a drama by choosing a story like a game or enjoy a game directed like a movie. These two media material interactive storytelling, and there have been discussions about them for many years. The purposes of this study are to propose a new branch structure for interactive storytelling and find a new perspective for the method of proceeding with a branch structure. The main research targeted a game that materialized interactive storytelling best. Based on the findings, the study proposed a volume branch structure including a plot border and adjuster concept for interactive storytelling to keep the story narrative and help the users feel interactions freely. This structure can be materialized only with real-time edited videos in the game media and will be possible in the application cases of a physical engine that continues to develop and artificial intelligence that has not been introduced in games actively.

• Journal of The Korean Association of Information Education
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• v.19 no.4
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• pp.441-448
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• 2015

This paper describes about a software implementation for class analysis and quantization based on our video synchronization method. We proposed a new indexing method, synchronization strategies, and data structure for our analyzer implementation. We implemented a class video analyzer using intelligent multimedia technologies which can play class video selectively. Our proposed method analyzes class videos depending on the time schedule composed of introduction, development and summary stages. We apply our analysis filters to the class videos in the predefined regular intervals. We experimented on the synchronization performance of our proposed method and software. In the experimental, we could demonstrate the effectiveness and practicality of our class analyzing method within the margin of error.

• Journal of the Korea Computer Graphics Society
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• v.21 no.5
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• pp.11-19
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• 2015

Our research introduces a novel system for creating 3D vehicle animation. Our system is for intuitively authoring vehicle accident scenes according to videos or based on user-drawn trajectories. Our system has been implemented by combining three existing ideas. The first part is for obtaining 3D trajectory of a vehicle from black-box videos. The second part is a tracking algorithm that controls a vehicle to follow a given trajectory with small errors. The last part optimizes the vehicle control parameters so that the error between the input trajectory and simulated vehicle trajectory is minimized. We also simulate the deformation of the car due to an impact to achieve believable results in real-time.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.51-56
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• 2020

In this paper, we developed a mobile new media solution that enables e-commerce shopping mall operators, band operators, and YouTube creators to create synergies in online and offline promotion by posting related video contents on the media in addition to their own videos. By providing videos in the field of the platform without directly searching for them, it is possible to provide users with a new type of marketing means that can promote their platform while providing interest and information. Prospective creators at home and abroad who produce video can upload their own video in addition to YouTube and afreeca TV, such as the open market for video, and use independent and free charging systems to manage independent customer relationship management(CRM), self-branding, and content management. It will be possible to utilize mobile-based new media equipped with a system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1027-1030
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• 2013

For the detection of objects in the videos, there are various ways that use the frequency transformation. In the videos, the images of objects could be changed slightly. Object detection methods using frequency transformation such as ASEF and MOSSE have the ability to renew the detection filter in order to deal with the change of object images. But these approaches are likely to fail the detection because the image changes often occur when they come out again after being hidden by other objects. What is worse, when they show up again, they appear in another place, not the original one. In this paper, a new proposal is present so that the detection can be carried out efficiently even when the images come out in other place, and the failure of the detection can be reduced.

• Management & Information Systems Review
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• v.39 no.3
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• pp.127-140
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• 2020

This study conducted analysis of YouTube channels by domestic companies as the marketing strategies of domestic companies vary due to the rapid growth of the Internet and YouTube channels. The YouTube channel analysis analyzed the number of subscribers, plays, videos and classifications of domestic companies on YouTube channels, the top 100 domestic companies in the YouTube ranking site "Company/Official. The analysis showed that 4.53 million companies had the largest number of subscribers, Samsung mobile, 544.69 million circuit Samsung mobile, and 11,416 League of Legends-Korea channels had the largest number of videos. The most product classification showed that food/dining companies were engaged in a lot of YouTube activities. The use of YouTube, which is rapidly growing in companies through analyzing YouTube channels from the perspective of a company's new marketing strategy, is a new tool for integrated marketing communications. It is expected that the YouTube channel, which enables two-way communication of companies' marketing strategies, will be used as basic data when producing YouTube content in the future.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.48-55
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• 2009

Prior research works in indoor-outdoor classification have been conducted based on a simple combination of low-level features. However, since there are many challenging problems due to the extreme variability of the scene contents, most methods proposed recently tend to combine the low-level features with high-level information such as the presence of trees and sky. To extract these regions from videos, we need to conduct additional tasks, which may yield the increasing number of feature dimensions or computational burden. Therefore, an efficient indoor-outdoor scene classification method is proposed in this paper. First, the video is divided into the five same-sized blocks. Then we define and use the edge and color orientation histogram (ECOH) descriptors to represent each sub-block efficiently. Finally, all ECOH values are simply concatenated to generated the feature vector. To justify the efficiency and robustness of the proposed method, a diverse database of over 1200 videos is evaluated. Moreover, we improve the classification performance by using different weight values determined through the learning process.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.37-45
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• 2008

Quality assessment ai s to evaluate if a distorted image or video has a good quality by measuring the difference between the original and distorted images or videos. In this paper, to assess the visual qualify of a distorted image or video, visual features of the distorted image are compared with those of the original image instead of the direct comparison of the distorted image with the original image. We use edge projections from two images as features, where the edge projection can be easily obtained by projecting edge pixels in an edge map along vertical/horizontal direction. In this paper, edge projections are obtained by using vertical/horizontal directions of gradients as well as the magnitude of each gradient. Experimental results show the effectiveness of the proposed quality assessment through the comparison with conventional quality assessment algorithms such as structural similarity(SSIM), edge peak signal-to-noise ratio(EPSNR), and edge histogram descriptor(EHD) methods.

• Journal of Korea Game Society
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• v.7 no.2
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• pp.33-40
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• 2007

Smoothing is a transmission plan where variable rate video data is converted to a constant bit rate stream. Among them are CBA, MCBA, MVBA and others. However, these smoothing algorithms produce a transmission plan where extra bandwidth in server is not considered. This may cause difficulty in providing videos to many clients in a server. In this paper, we propose the smoothing algorithm with monotonic transmission rate increase and abrupt transmission rate decrease, in order to provide videos to as many clients in server with limited network bandwidth as possible. In order to show the performance of our proposed algorithm, various evaluation factors were used such as the maximum number of clients, the average number of clients, and so on. Experiments demonstrated that the proposed algorithm outperformed other algorithms in evaluation factors such as the maximum number of clients and the average number of clients.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1134-1142
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• 2019

Detection of double compression is one of the most efficient ways of remarking the validity of videos. Many methods have been introduced to detect HEVC double compression with different coding parameters. However, HEVC double compression detection under the same coding environments is still a challenging task in video forensic. In this paper, we introduce a novel method based on the frame partitioning information in intra prediction mode for detecting double compression in with the same coding environments. We propose to extract statistical feature and Deep Convolution Neural Network (DCNN) feature from the difference of partitioning picture including Coding Unit (CU) and Transform Unit (TU) information. Finally, a softmax layer is integrated to perform the classification of the videos into single and double compression by combing the statistical and the DCNN features. Experimental results show the effectiveness of the statistical and the DCNN features with an average accuracy of 87.5% for WVGA and 84.1% for HD dataset.