• Title/Summary/Keyword: Video editing

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Video Automatic Editing Method and System based on Machine Learning (머신러닝 기반의 영상 자동 편집 방법 및 시스템)

  • Lee, Seung-Hwan;Park, Dea-woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.235-237
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    • 2022
  • Video content is divided into long-form video content and short-form video content according to the length. Long form video content is created with a length of 15 minutes or longer, and all frames of the captured video are included without editing. Short-form video content can be edited to a shorter length from 1 minute to 15 minutes, and only some frames from the frames of the captured video. Due to the recent growth of the single-person broadcasting market, the demand for short-form video content to increase viewers is increasing. Therefore, there is a need for research on content editing technology for editing and generating short-form video content. This study studies the technology to create short-form videos of main scenes by capturing images, voices, and motions. Short-form videos of key scenes use a pre-trained highlight extraction model through machine learning. An automatic video editing system and method for automatically generating a highlight video is a core technology of short-form video content. Machine learning-based automatic video editing method and system research will contribute to competitive content activities by reducing the effort and cost and time invested by single creators for video editing

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Multi-Sever based Distributed Coding based on HEVC/H.265 for Studio Quality Video Editing

  • Kim, Jongho;Lim, Sung-Chang;Jeong, Se-Yoon;Kim, Hui-Yong
    • Journal of Multimedia Information System
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    • v.5 no.3
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    • pp.201-208
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    • 2018
  • High Efficiency Video Coding range extensions (HEVC RExt) is a kind of extension model of HEVC. HEVC RExt was specially designed for dealing the high quality images. HEVC RExt is very essential for studio editing which handle the very high quality and various type of images. There are some problems to dealing these massive data in studio editing. One of the most important procedure is re-encoding and decoding procedure during the editing. Various codecs are widely used for studio data editing. But most of the codecs have common problems to dealing the massive data in studio editing. First, the re-encoding and decoding processes are frequently occurred during the studio data editing and it brings enormous time-consuming and video quality loss. This paper, we suggest new video coding structure for the efficient studio video editing. The coding structure which is called "ultra-low delay (ULD)". It has the very simple and low-delayed referencing structure. To simplify the referencing structure, we can minimize the number of the frames which need decoding and re-encoding process. It also prevents the quality degradation caused by the frequent re-encoding. Various fast coding algorithms are also proposed for efficient editing such as tool-level optimization, multi-serve based distributed coding and SIMD (Single instruction, multiple data) based parallel processing. It can reduce the enormous computational complexity during the editing procedure. The proposed method shows 9500 times faster coding speed with negligible loss of quality. The proposed method also shows better coding gain compare to "intra only" structure. We can confirm that the proposed method can solve the existing problems of the studio video editing efficiently.

A Systematic Mapping Study on Artificial Intelligence Tools Used in Video Editing

  • Bieda, Igor;Panchenko, Taras
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.312-318
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    • 2022
  • From the past two eras, artificial intelligence has gained the attention of researchers of all research areas. Video editing is a task in the list that starts leveraging the blessing of Artificial Intelligence (AI). Since AI promises to make technology better use of human life although video editing technology is not new yet it is adopting new technologies like AI to become more powerful and sophisticated for video editors as well as users. Like other technologies, video editing will also be facilitated by the majestic power of AI in near future. There has been a lot of research that uses AI in video editing, yet there is no comprehensive literature review that systematically finds all of this work on one page so that new researchers can find research gaps in that area. In this research we conducted a statically approach called, systematic mapping study, to find answers to pre-proposed research questions. The aim and objective of this research are to find research gaps in our topic under discussion.

Video Editing System Considering Smart Phone Playback Environment (스마트폰 재생환경을 고려한 동영상 편집 시스템)

  • O, Junsol;Lee, Hyunjung;Park, Chun-Su
    • Journal of the Semiconductor & Display Technology
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    • v.16 no.1
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    • pp.75-80
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    • 2017
  • Nowadays, smart phone is being popularly used for communication, entertainment, and information retrieval. While demands on video traffic over mobile networks increases sharply, the wireless link capacity is often limited to fully support the traffic demand. Therefore, the size of video data needs to be reduced to provide high quality video with limited capacity. To handle this issue, we propose a video editing system using the ffmpeg library. The proposed system can provide a high quality video with a relatively small data size, thereby facilitating the mobile streaming services and live-video games.

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News Video Editing System (뉴스비디오 편집시스템)

  • 고경철;이양원
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2000.10a
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    • pp.421-425
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    • 2000
  • The efficient researching of the News Video is require the development of video processing and editing technology to extract meaningful information from the Video data. The advanced information nations are researching the Video Editing System and recently they are concerned to research the perfect practical system. This paper represents the System that can extract and edit the meaningful information from the Video Data by the User demand through the Scene change detection and Editing system by the automatic/ passive classification and this system represents more efficient scene change detection algorithm which was selected by the user.

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An Optimal Video Editing Method using Frame Information Pre-Processing (프레임 정보 전처리를 활용한 최적 영상 편집 방법)

  • Lee, Jun-Pyo;Cho, Chul-Young;Lee, Jong-Soon;Kim, Tae-Yeong;Kwon, Cheol-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.7
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    • pp.27-32
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    • 2010
  • We can cut and paste portions of MPEG coded bitstream efficiently to rearrange the audio and video sequences using our proposed method. The proposed method decodes the MPEG stream within just only one GOP(Group of Picture), edits the decoded video frames, and encodes it back to a MPEG stream. In this method, precise editing is possible. A pre-processing step is specially designed to provide easy cut and paste processing. In the pre-processing step for editing MPEG streams, the detail information is extracted. In addition, video quality is not degraded after the proposed editing process is applied. Consequently, the experimental results show significant improvements compared with traditional algorithms for video editing method in terms of the efficiency and exactness.

Video Content Editing System for Senior Video Creator based on Video Analysis Techniques (영상분석 기술을 활용한 시니어용 동영상 편집 시스템)

  • Jang, Dalwon;Lee, Jaewon;Lee, JongSeol
    • Journal of Broadcast Engineering
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    • v.27 no.4
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    • pp.499-510
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    • 2022
  • This paper introduces a video editing system for senior creator who is not familiar to video editing. Based on video analysis techniques, it provide various information and delete unwanted shot. The system detects shot boundaries based on RNN(Recurrent Neural Network), and it determines the deletion of video shots. The shots can be deleted using shot-level significance, which is computed by detecting focused area. It is possible to delete unfocused shots or motion-blurred shots using the significance. The system detects object and face, and extract the information of emotion, age, and gender from face image. Users can create video contents using the information. Decorating tools are also prepared, and in the tools, the preferred design, which is determined from user history, places in the front of the design element list. With the video editing system, senior creators can make their own video contents easily and quickly.

The Procedural Design and Evaluation of RPT Learning Model for NLE Beginners (비선형 편집 입문자를 위한 RPT 학습모형 절차 설계 및 평가)

  • Jang, Kyeong-Su
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.4
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    • pp.163-172
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    • 2017
  • In recent days, the Non-Linear Editing is mainly used in the field of broadcasting. In comparison to conventional editing, Non-Linear Editing can immediately access the image of the desired position and facilitate the insertion and deletion of video frame. Furthermore, it directly apply a title and transition effect to video frame. Moreover, it has an advantage of preview and easy modification in title effect, transition and editing prior to export. However, students who learn Non-Linear Editing first time are not easy to learn it. In this paper, we propose a new learning model based on Reciprocal Peer Teaching (RPT), which helps NLE beginners to understand Non-Linear editing more clearly. We divide the students into two groups i.e. control group and experimental group. The control group students do not apply proposed method while experimental group performs evaluation over our model. Furthermore, we carry out the experiments, which include the overall average of the two groups, academic achievement of students with low grades, standard deviation, T-test and satisfaction surveys. The experimental group shows the superiority in performed experiments and higher satisfaction ratings than the control group.

A Study on Tapeless HD Format Editing -Focus on video editing using PMW-EX3 and Avid Media Composer- (테이프리스 기반의 HD포맷 편집에 관한 연구 -PMW-EX3와 Avid Media Composer를 이용한 영상편집 중심으로-)

  • Park, Sung-Dae;Han, Soo-Whan
    • Journal of Digital Contents Society
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    • v.10 no.3
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    • pp.461-468
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    • 2009
  • In a recent year, the broadcasting system has been changed from analogue to digital all over the world, not just in Korea, and Korea aims at accomplishing 100% digital broadcasting by 2013. The HD(High Definition) Video Format, which currently plays a key role in digital broadcasting system, has been gradually extended in the field of broadcasting and movie. Additionally, many kinds of camcoders and editing systems have been rapidly converted into the digital types, and they are supporting to photograph and video editing systems with the various types of image formats such as SD(Standard Definition) format, HD format, 2K, 4K, etc. Tape Video Storage System, which has been usually used in the stage of photographing by this day, is gradually evolving into Tapeless Video Data Storage System. Thus in this study, Video Compression method of HD format photographed by Sony PMW-EX3, one of major tapeless camcoders, is studied and also the way of applying it effectively in Avid Media Composer, a non-linear editing system, is discussed.

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Video Editing using Hand Gesture Tracking and Recognition (손동작 추적 및 인식을 이용한 비디오 편집)

  • Bae, Cheol-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.1
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    • pp.102-107
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    • 2007
  • In this paper presents a gesture based driven approach for video editing. Given a lecture video, we adopt novel approaches to automatically detect and synchronize its content with electronic slides. The gestures in each synchronized topic (or shot) are then tracked and recognized continuously. By registering shots and slides md recovering their transformation, the regions where the gestures take place can be known. Based on the recognized gestures and their registered positions, the information in slides can be seamlessly extracted not only to assist video editing, but also to enhance the quality of original lecture video. In experiment with two videos, the proposed system showd each gesture recognition rate 95.5%,96.4%.