• Title/Summary/Keyword: Videos

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YouTube Video Content Analysis: Focusing on Korean Dance Videos (유튜브(YouTube) 영상 콘텐츠 분석: 국내 무용 영상을 중심으로)

  • Suejung Chae;Jihae Suh
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.1-13
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    • 2023
  • The widespread adoption of smartphones and advancements in internet technology have notably shifted content consumption habits toward video. This research aims to dissect the nature of videos posted on YouTube, the global video-sharing platform, to understand the characteristics of both produced and preferred content. For this study, dance was chosen as a specific subject from a variety of video categories. Data on YouTube videos associated with the term "dance" was compiled over three years, from 2019 to 2021. The investigation revealed a clear distinction between the types of dance videos frequently uploaded to YouTube and those that receive a high number of views. The empirical analysis of this study indicates a viewer preference for vlogs that provide insights into the daily lives of dance students, as well as for purpose-driven videos, such as those highlighting dance exam preparations or school dance events. Notably, the vlogs that attract the most attention are typically created by dance students at the college or secondary school level, rather than by professionals. Although the study was focused on dance, its methodologies can be applied to different subjects. These insights are expected to contribute to the development of a recommendation system that aids content creators in effectively targeting their productions.

Affective Effect of Video Playback Style and its Assessment Tool Development (영상의 재생 스타일에 따른 감성적 효과와 감성 평가 도구의 개발)

  • Jeong, Kyeong Ah;Suk, Hyeon-Jeong
    • Science of Emotion and Sensibility
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    • v.19 no.3
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    • pp.103-120
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    • 2016
  • This study investigated how video playback styles affect viewers' emotional responses to a video and then suggested emotion assessment tool for playback-edited videos. The study involved two in-lab experiments. In the first experiment, observers were asked to express their feelings while watching videos in both original playback and articulated playback simultaneously. By controlling the speed, direction, and continuity, total of twelve playback styles were created. Each of the twelve playback styles were applied to five kinds of original videos that contains happy, anger, sad, relaxed, and neutral emotion. Thirty college students participated and more than 3,800 words were collected. The collected words were comprised of 899 kinds of emotion terms, and these emotion terms were classified into 52 emotion categories. The second experiment was conducted to develop proper emotion assessment tool for playback-edited video. Total of 38 emotion terms, which were extracted from 899 emotion terms, were employed from the first experiment and used as a scales (given in Korean and scored on a 5-point Likert scale) to assess the affective quality of pre-made video materials. The total of eleven pre-made commercial videos which applied different playback styles were collected. The videos were transformed to initial (un-edited) condition, and participants were evaluated pre-made videos by comparing initial condition videos simultaneously. Thirty college students evaluated playback-edited video in the second study. Based on the judgements, four factors were extracted through the factor analysis, and they were labelled "Happy", "Sad", "Reflective" and "Weird (funny and at the same time weird)." Differently from conventional emotion framework, the positivity and negativity of the valence dimension were independently treated, while the arousal aspect was marginally recognized. With four factors from the second experiment, finally emotion assessment tool for playback-edited video was proposed. The practical value and application of emotion assessment tool were also discussed.

Automatic Summarization of Basketball Video Using the Score Information (스코어 정보를 이용한 농구 비디오의 자동요약)

  • Jung, Cheol-Kon;Kim, Eui-Jin;Lee, Gwang-Gook;Kim, Whoi-Yul
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.9C
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    • pp.881-887
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    • 2007
  • In this paper, we proposed a method for content based automatic summarization of basketball game videos. For meaningful summary, we used the score information in basketball videos. And the score information is obtained by recognizing the digits on the score caption and analyzing the variation of the score. Generally, important events of basketball are the 3-point shot, one-sided runs, the lead changes, and so on. We have detected these events using score information and made summaries and highlights of basketball video games.

Integrated Management System for Vehicle Black Box Video Using Mobile Cloud (모바일 클라우드를 이용한 차량용 블랙박스 영상 통합관리 시스템)

  • Jeong, Seong-Woo;Park, Yoo-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.10
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    • pp.2352-2358
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    • 2013
  • In this paper, we designed and implemented black box terminal with wireless communication function and cloud server for more efficient usage of black box video. Our system can store and manage all vehicle black box videos so public institutions can select videos with various conditions such as object, time-based and location based like integrated CCTV management system.

Real-Time License Plate Detection in High-Resolution Videos Using Fastest Available Cascade Classifier and Core Patterns

  • Han, Byung-Gil;Lee, Jong Taek;Lim, Kil-Taek;Chung, Yunsu
    • ETRI Journal
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    • v.37 no.2
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    • pp.251-261
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    • 2015
  • We present a novel method for real-time automatic license plate detection in high-resolution videos. Although there have been extensive studies of license plate detection since the 1970s, the suggested approaches resulting from such studies have difficulties in processing high-resolution imagery in real-time. Herein, we propose a novel cascade structure, the fastest classifier available, by rejecting false positives most efficiently. Furthermore, we train the classifier using the core patterns of various types of license plates, improving both the computation load and the accuracy of license plate detection. To show its superiority, our approach is compared with other state-of-the-art approaches. In addition, we collected 20,000 images including license plates from real traffic scenes for comprehensive experiments. The results show that our proposed approach significantly reduces the computational load in comparison to the other state-of-the-art approaches, with comparable performance accuracy.

Online-Based Local Government Image Typology: A Case Study on Jakarta Provincial Government Official YouTube Videos

  • Pratama, Arif Budy
    • Journal of Contemporary Eastern Asia
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    • v.16 no.1
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    • pp.1-21
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    • 2017
  • The Jakarta Provincial Government utilizes the YouTube channel to interact with citizens and enhance transparency. The purpose of this study is to explore online perceptions of local government image perceived by online audiences through the YouTube platform. The concepts of organizational image and credibility in the political image are adapted to analyze online public perceptions on the Jakarta Provincial Government image. Using the video summarization approach on Three hundred and forty-six official YouTube videos, which were uploaded from 1 March 2016 to 31 May 2016, and content analysis of Eight thousand two hundred and thirty-seven comments, this study shows both political and bureaucratic image emerge concurrently in the Jakarta Provincial Government case. The typology model is proposed to describe and explain the four image variations that occurred in the case study. Practical recommendations are suggested to manage YouTube channel as one of the social media used in the local government context.

People Detection Algorithm in the Beach (해변에서의 사람 검출 알고리즘)

  • Choi, Yu Jung;Kim, Yoon
    • Journal of Korea Multimedia Society
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    • v.21 no.5
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    • pp.558-570
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    • 2018
  • Recently, object detection is a critical function for any system that uses computer vision and is widely used in various fields such as video surveillance and self-driving cars. However, the conventional methods can not detect the objects clearly because of the dynamic background change in the beach. In this paper, we propose a new technique to detect humans correctly in the dynamic videos like shores. A new background modeling method that combines spatial GMM (Gaussian Mixture Model) and temporal GMM is proposed to make more correct background image. Also, the proposed method improve the accuracy of people detection by using SVM (Support Vector Machine) to classify people from the objects and KCF (Kernelized Correlation Filter) Tracker to track people continuously in the complicated environment. The experimental result shows that our method can work well for detection and tracking of objects in videos containing dynamic factors and situations.

Graph-Based framework for Global Registration (그래프에 기반한 전역적 정합 방법)

  • 김현우;홍기상
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.671-674
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    • 2000
  • In this paper, we present a robust global registration algorithm for multi-frame image mosaics. When we perform a pair-wise registration recovering a projective transformation between two consecutive frames, severe mis-registration among multiple frames, which are not consecutive, can be detected. It is because the concatenation of those pair-wise transformations leads to global alignment errors. To overcome those mis-registrations, we propose a new algorithm using multiple frames for constructing image mosaics. We use a graph to represent the temporal and spatial connectivity and show that global registration can be obtained through the search for an optimal path in the constructed graph. The definition of an adequate objective function characterizing the global registration provides a direct manipulation of the graph. In the presence of moving objects, especially large ones compared with low texture backgrounds, by using the likelihood ratio as the objective function, we can deal with some of the most challenging videos like basketball or soccer Moreover, the algorithm can be parallelized so it can be more efficiently implemented. Finally, we give some experimental results from real videos.

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Development of Video Data-base and a Video Annotation Tool for Evaluation of Smart CCTV System (지능형CCTV시스템 성능평가를 위한 영상DB와 영상 주석도구 개발)

  • Park, Jang-Sik;Yi, Seung-Jai
    • The Journal of the Korea institute of electronic communication sciences
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    • v.9 no.7
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    • pp.739-745
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    • 2014
  • In this paper, an evaluation of intelligent CCTV system is proposed with recording and implementation video and video DB. Videos for evaluation are recorded by dividing far, mid and near zone. Video DB has video recording information, detection area, and ground truth in XML format. A video annotation tool is proposed to make ground truth effectively in this paper. A video annotation tool writes ground truths of videos and includes evaluation comparing system alarms with ground truths.