• 한국정보처리학회논문지
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• 제6권10호
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• pp.2790-2796
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• 1999

In video-on-demand systems, the I.O bandwidth of video servers is the critical resource which contributes to increase in latency. Several approaches: bridging, piggybacking are used to reduce the I/O demand on the video server through sharing. Batching delays the requests for the different videos for a batching window so that more requests for the same video arriving during the current batching window may be served using the same stream. In this paper, we propose an adaptive reservation-based batching policy which dynamically reserves video server capacity for popoular videos according to video server loads. The performance of the proposed policy is evaluated through a simulation, and is compared with simple batching and static reservation-based batching policies. As the result, we know that the adaptive reservation-based batching policy more improves service ratio and average waiting time than simple batching and simple reservation-based batching policy more improves service ratio and average waiting time than simple batching and simple reservation-based batching polices.

• 한국문헌정보학회지
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• 제51권1호
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• pp.227-243
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• 2017

This study proposed a structural and semantic framework for the characterization of events and segments in Web videos that permits content-based searches and dynamic video summarization. Although MPEG-7 supports multimedia structural and semantic descriptions, it is not currently suitable for describing multimedia content on the Web. Thus, the proposed metadata framework that was designed considering Web environments provides a thorough yet simple way to describe Web video contents. Precisely, the metadata framework was constructed on the basis of Chatman's narrative theory, three multimedia metadata formats (PBCore, MPEG-7, and TV-Anytime), and social metadata. It consists of event information, eventGroup information, segment information, and video (program) information. This study also discusses how to automatically extract metadata elements including structural and semantic metadata elements from Web videos.

• 한국컴퓨터정보학회논문지
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• 제23권9호
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• pp.27-34
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• 2018

Personal media centered on blogs, Twitter, and Facebook has opened up a personal broadcasting area while meeting platforms such as YouTube and Africa TV. Due to the many advantages and disadvantages of personal broadcasting, a study on it was necessary and statistical survey was conducted. The study conducted opinion survey of 118 university students on personal broadcasting. As a result, we are getting news using smartphones and mainly watching videos through YouTube, and watching videos type in the order of games, music videos and sports. Satisfaction rate of video was 72.4%, 80.2% of survey did not use paid services, experiences about personal broadcasting was 96.6% and 90.5% of survey the prospect of person broadcasting of the opinion that "it will be expanded". The first thing we want to be improved in personal broadcasting is the prevention of abusive language and hate speech. Second, we were reluctant to sensational content. Third, the survey results are the improvement of excessive advertising.

• Journal of Multimedia Information System
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• 제5권4호
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• pp.257-264
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• 2018

Over the years application of computer vision techniques in sports videos for analysis have garnered interest among researchers. Videos of sports games like basketball, football are available in plenty due to heavy popularity and coverage. The goal of the researchers is to extract information from sports videos for analytics which requires the tracking of the players. In this paper, we explore use of deep learning networks for player spotting and propose an algorithm for tracking using Kalman filters. We also propose an algorithm for finding distance covered by players. Experiments on sports video datasets have shown promising results when compared with standard techniques like mean shift filters.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.957-966
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• 2019

This paper studies a novel approach to natural gait cycles based gait recognition via kernel Fisher discriminant analysis (KFDA), which can effectively calculate the features from gait sequences and accelerate the recognition process. The proposed approach firstly extracts the gait silhouettes through moving object detection and segmentation from each gait videos. Secondly, gait energy images (GEIs) are calculated for each gait videos, and used as gait features. Thirdly, KFDA method is used to refine the extracted gait features, and low-dimensional feature vectors for each gait videos can be got. The last is the nearest neighbor classifier is applied to classify. The proposed method is evaluated on the CASIA and USF gait databases, and the results show that our proposed algorithm can get better recognition effect than other existing algorithms.

• 한국전자통신학회논문지
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• 제16권1호
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• pp.81-88
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• 2021

최근 COVID-19로 인한 온라인 강의 영상과 같은 많은 영상이 생성되고 있는데 노동 시간의 한계와 비용의 부족 등으로 인해 자막을 보유한 영상이 일부분에 불과하여 청각장애인들의 정보 취득에 방해 요소로 대두되고 있다. 본 논문에서는 음성인식을 이용하여 자막을 자동으로 생성하고 종결 어미와 시간을 이용해 문장을 분리하여 자막을 생성함으로써 자막 생성에 드는 시간과 노동력을 줄일 수 있도록 하는 시스템을 개발하고자 한다.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.571-585
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• 2021

Applications for object detection are expanding as it is automated through artificial intelligence-based processing, such as deep learning, on a large volume of images and videos. High dependence on training data and a non-transparent way to find answers are the common characteristics of deep learning. Attacks on training data and training models have emerged, which are closely related to the nature of deep learning. Privacy, integrity, and robustness for the extracted information are important security issues because deep learning enables object recognition in images and videos. This paper summarizes the security issues that need to be addressed for future applications and analyzes the state-of-the-art security studies related to robustness, privacy, and integrity of object detection for images and videos.

• Journal of Multimedia Information System
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• 제8권4호
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• pp.243-250
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• 2021

Instructional contents are used to demonstrate a technical process to teach and walkthrough certain procedures to carry out a task. This type of informational content is widely used for teaching and lectures in form of tutorial videos and training videos. Since there are questions and uncertainties for what could be the killer application for the novel wearables, we propose a self-instruction training application on a smart glass to utilize already-available instruction videos as well as public open data in creative ways. We design and implement a prototype application to help users train by wearing smart glasses specifically designed for two concrete and hand-constrained use cases where the user's hands need to be free to operate. To increase the efficiency and feasibility of the self-instruction training, we contribute to the development of a wearable killer application by integrating a voice-based user interface using speech recognizer, public open data APIs, and timestamp-based procedural content navigation structure into our proof-of-concept application.

• International Journal of Computer Science & Network Security
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• 제23권3호
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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%.

• 감성과학
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• 제25권3호
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• pp.47-62
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• 2022

이전 정서연구에서는 다양한 정서유발자극을 이용한 정서 차원 연구들을 통해 쾌불쾌 차원(valence)과 각성 차원(arousal)이란 두 가지의 핵심정서(core affect) 차원을 밝혔다. 최근 등장한 ASMR은 심리적 안정감, 편안함 등의 정서를 유발하는데, 이런 새로운 자극 또한 핵심정서차원에 위치하는지, 사람들에게 일으키는 정서표상은 어떤 양상을 보이는지 확인하고자 하였다. 본 연구는 3가지 정서유형(부정, 중립, 긍정)으로 구분한 ASMR 영상을 자극으로 사용하였다. 연구1에서는 청각 ASMR, 연구2에서는 청각 및 시청각 ASMR을 자극으로 사용하였고, 각 자극마다 10가지의 형용사에 대해 5점 리커트 척도로 정서경험을 보고받았다. 자료수집 이후 다차원척도법과 분류분석을 실시하였다. 다차원척도법 결과, 청각 및 시청각 ASMR 모두 핵심정서차원인 쾌불쾌 차원에서 잘 구분되었다. 분류분석 결과, 동일한 감각양상 및 서로 다른 감각양상의 ASMR에 대한 참가자 개인의 정서표상 구분과 참가자들간 정서표상 구분이 잘 이뤄졌다. 종합적으로 본 연구는 다른 정서유발자극들과 같이 ASMR 또한 핵심정서차원에 위치한다는 것을 시사한다는 점에서 기존의 Russell(1980)의 핵심정서차원 이론을 지지한다. 또한, 감각양상에 상관없이 ASMR에 대한 참가자 개인의 정서표상이 예측가능하며, 참가자들의 정서표상이 일관적이라는 점을 시사한다.