• Title/Summary/Keyword: Scene analysis

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An analysis on the mask play music composition - focuscing on the Bonsandaenori mask play - (가면극 음악구성의 원리 - 본산대놀이계통 가면극을 중심으로 -)

  • Im, Hyejung
    • (The) Research of the performance art and culture
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    • no.33
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    • pp.97-128
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    • 2016
  • According to the findings of the study, the music composition of the mask play is deeply related to the main characteristics of the scene. The first scene of the play starts with the Byeoksa dance. This particular dance part represents the evil spirit expel ritual. The instrumental accompaniment like and are played for the dance. The last part of the play starts with the Halmi and Yeonggam scene. This scene is played in both the instrumental and vocal music. For the instrumental part , for the vocal part and songs are played. and songs are played on the part of the Halmi's funeral ceremony scene. The instrumental and are played in various scenes for the accompaniment of the dance part. The musical structure of the mask play is flexible. This kind of flexibility of scene structure mainly concerned with the way of musical composition. The main structure of the mask play can be classified into two main styles according to the allocation of the vocal music. In first style, the vocal music is evenly dispersed. In second style, the vocal parts are concentrated in the rear section. As I mentioned earlier, no logical association is found in the matter of the scene arrangement. A scene arrangement has a deep connection with the arrangement of the music in each scene. In conclusion, the mixed arrangement of the scene in mask play is mainly concerned with the matter of the music arrangement in order to maintain the tension of the drama.

A Study on depth analysis for S3D animation (S3D 애니메이션 제작을 위한 입체 값 분석 기술)

  • Kim, Sang-hoon;hwan, Moon suk
    • Journal of Digital Contents Society
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    • v.16 no.4
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    • pp.645-650
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    • 2015
  • In this paper, we propose the method for creating a stable stereoscopic 3D contents with the production guidelines by removing the excessive depth value and scene changes for high quality. We have developed a three-dimensional depth analysis tool for detecting the scene changes out of the production guidelines and the depth value changes excessively. The Scenes detected by depth analysis tool can be modified at the post production and it helps to make a stable stereoscopic 3D contents.

Acoustic scene classification using recurrence quantification analysis (재발량 분석을 이용한 음향 상황 인지)

  • Park, Sangwook;Choi, Woohyun;Ko, Hanseok
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.1
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    • pp.42-48
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    • 2016
  • Since a variety of sound occur in same place and similar sound occurs in other places, the performance of acoustic scene classification is not guaranteed in case of insufficient training data. A Bag of Words (BOW) based histogram feature is foreseen as a method to overcome the problem. However, since the histogram features is made by using a feature distribution, the ordering of sequence of features is ignored. A temporal information such as periodicity and stationarity are also important for acoustic scene classification. In this paper, temporal features about a periodicity and a stationarity are extracted by using a recurrent quantification analysis. In the experiment, performance of the proposed method is shown better than other baseline methods.

Detection of Abnormal Behavior by Scene Analysis in Surveillance Video (감시 영상에서의 장면 분석을 통한 이상행위 검출)

  • Bae, Gun-Tae;Uh, Young-Jung;Kwak, Soo-Yeong;Byun, Hye-Ran
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.12C
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    • pp.744-752
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    • 2011
  • In intelligent surveillance system, various methods for detecting abnormal behavior were proposed recently. However, most researches are not robust enough to be utilized for actual reality which often has occlusions because of assumption the researches have that individual objects can be tracked. This paper presents a novel method to detect abnormal behavior by analysing major motion of the scene for complex environment in which object tracking cannot work. First, we generate Visual Word and Visual Document from motion information extracted from input video and process them through LDA(Latent Dirichlet Allocation) algorithm which is one of document analysis technique to obtain major motion information(location, magnitude, direction, distribution) of the scene. Using acquired information, we compare similarity between motion appeared in input video and analysed major motion in order to detect motions which does not match to major motions as abnormal behavior.

Application of Shape Analysis Techniques for Improved CASA-Based Speech Separation (CASA 기반 음성분리 성능 향상을 위한 형태 분석 기술의 응용)

  • Lee, Yun-Kyung;Kwon, Oh-Wook
    • MALSORI
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    • no.65
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    • pp.153-168
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    • 2008
  • We propose a new method to apply shape analysis techniques to a computational auditory scene analysis (CASA)-based speech separation system. The conventional CASA-based speech separation system extracts speech signals from a mixture of speech and noise signals. In the proposed method, we complement the missing speech signals by applying the shape analysis techniques such as labelling and distance function. In the speech separation experiment, the proposed method improves signal-to-noise ratio by 6.6 dB. When the proposed method is used as a front-end of speech recognizers, it improves recognition accuracy by 22% for the speech-shaped stationary noise condition and 7.2% for the two-talker noise condition at the target-to-masker ratio than or equal to -3 dB.

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Semantic Scenes Classification of Sports News Video for Sports Genre Analysis (스포츠 장르 분석을 위한 스포츠 뉴스 비디오의 의미적 장면 분류)

  • Song, Mi-Young
    • Journal of Korea Multimedia Society
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    • v.10 no.5
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    • pp.559-568
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    • 2007
  • Anchor-person scene detection is of significance for video shot semantic parsing and indexing clues extraction in content-based news video indexing and retrieval system. This paper proposes an efficient algorithm extracting anchor ranges that exist in sports news video for unit structuring of sports news. To detect anchor person scenes, first, anchor person candidate scene is decided by DCT coefficients and motion vector information in the MPEG4 compressed video. Then, from the candidate anchor scenes, image processing method is utilized to classify the news video into anchor-person scenes and non-anchor(sports) scenes. The proposed scheme achieves a mean precision and recall of 98% in the anchor-person scenes detection experiment.

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A Sensor Module Overcoming Thick Smoke through Investigation of Fire Characteristics (화재 특성 고찰을 통한 농연 극복 센서 모듈)

  • Cho, Min-Young;Shin, Dong-In;Jun, Sewoong
    • The Journal of Korea Robotics Society
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    • v.13 no.4
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    • pp.237-247
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    • 2018
  • In this paper, we describe a sensor module that monitors fire environment by analyzing fire characteristics. We analyzed the smoke characteristics of indoor fire. Six different environments were defined according to the type of smoke and the flame, and the sensors available for each environment were combined. Based on this analysis, the sensors were selected from the perspective of firefighter. The sensor module consists of an RGB camera, an infrared camera and a radar. It is designed with minimum weight to fit on the robot. the enclosure of sensor is designed to protect against the radiant heat of the fire scene. We propose a single camera mode, thermal stereo mode, data fusion mode, and radar mode that can be used depending on the fire scene. Thermal stereo was effectively refined using an image segmentation algorithm, SLIC (Simple Linear Iterative Clustering). In order to reproduce the fire scene, three fire test environments were built and each sensor was verified.

Scene extraction technology on deep learning for media production (미디어 제작을 위한 씬 검출 기법)

  • Song, Hyok;Ko, Min-Soo;Yoo, Jisang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.184-185
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    • 2022
  • 인터넷 환경의 변화에 따라 텍스트 기반의 정보 전달에서 멀티미디어 기반의 스트리밍 방식으로 바뀌어가고 있다. 또한 대용량의 동영상 데이터뿐 아니라 Shorts, Clip Reels 또는 등 다양한 방식의 동영상 형태로 배포되고 있으며 서비스 플랫폼에서는 손쉽게 편집할 수 있도록 기능을 제공하고 있다. 대용량 콘텐츠, TV, Youtue 콘텐츠를 포함하여 소용량 동영상 편집에 필요한 영상 제작 기술에서 가장 인력과 시간이 많이 소요되는 부분은 편집 단계로 딥러닝 기반 인공지능 기술을 활용하여 자동화하고 있으며 영상편집에서 가장 기본이 되는 단위인 씬검출 기법을 개발하였다. 키프레임 검출 기법과 유사도 기법을 이용하여 씬을 추출하였으며 블록 Cost Function을 이용하여 최적화하여 0.5214의 정확도를 도출하였다.

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Mirror vision for car Black box (자동차 블랙박스를 위한 미러 비전)

  • Kim, Eun-Ho;Lim, Myoung-Sub
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.369-372
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    • 2007
  • about commercial business of car black box, mirror vision for car black box deal with analysis of Existing Car Black boxes in market to provide the objective information associated with surrounding scene of car instead of witness, we experimented on suitable structure of all direction to cover surrounding of car considering dead zone where can't see at short distance and realized simple structure of gathering scene using mirror and lens and by saving the number of camera and MUX of pre-circut

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A Scene Boundary Detection Scheme using Audio Information in MPEG System Stream (MPEG 시스템 스트림상에서 오디오 정보를 이용한 장면 경계 검출 방법)

  • Kim, Jae-Hong;Nang, Jong-Ho;Park, Soo-Yong
    • Journal of KIISE:Software and Applications
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    • v.27 no.8
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    • pp.864-876
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    • 2000
  • This paper proposes a new scene boundary detection scheme for the MPEG System stream using MPEG Audio information and proves its usefulness by extensive experiments. A scene boundary has a characteristic that the audio as well as video information are changed rapidly. This paper first classifies this scene boundary into three cases ; Radical, Gradual, Micro Changes, with respect to the audio changes. The Radical change has a large-scale changing of decibel value and pitch value at a scene boundary, the Gradual change shows the long-time transition of decibel and pitch values from max to min or vice versa, and the Micro change displays a some change of pitch or frequency distribution without decibel changes. Upon this analysis, a new scene change detection algorithm detecting these three cases is proposed in which a progressive window with a time line is used to trace the changes in the audio information. Some experiments with various movies show that proposed algorithm could produce a high detection ratio for Radical change that is the most popular scene change in the movies, while producing a moderate detection ratio for Gradual and Micro changes. The proposed scene boundary detection scheme could be used to build a database for visual information like MPEG System stream.

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