• Title/Summary/Keyword: 경계추출

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A Study of Medium Shot Detection (미디엄 숏 검출에 관한 연구)

  • Hyung Lee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.93-95
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    • 2023
  • 본 논문에서는 장편의 드라마나 영화에서 스토리 기반의 축약된 요약본을 자동으로 제작하기 위해 미디엄 숏(medium shot) 크기의 숏(shot)들을 추출하기 위한 방법을 고려한다. 미디엄 숏 정도의 크기는 보통 인물에 중심을 둔 숏들로 인물들 간의 관계에서 특히 대사나 표정으로 내용을 전달하기 위한 목적으로 적극 권장된다. 비디오 검색을 위한 인덱싱에서 신(scene) 전환 검출 및 숏 경계 검출, 그리고 이미지에서 심도와 초점기반의 화질 및 피사체 추출 등을 위해 전통적인 신호/영상처리 기법의 활용에서부터 최근의 기계학습 접목 등 다양한 연구들이 진행되고 있다. 영상문법에 근거하여 편집된 영상물에서 미디엄 숏 정도 크기의 숏들을 추출하여 배열한다면 어느 정도 원본 내용을 충실히 전달할 수 있는 축약된 요약본을 제작할 수 있다는 가정하에 해당 샷들을 블러(blur) 기반으로 검출하기 위해 이와 관련된 키워드들을 기반으로 기존 연구들을 살펴보고 적용 방법을 모색한다.

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A Study on extraction for Korean-English word pair by using LCS algorithm (LCS알고리즘을 이용한 한-영 대역어 추출 연구)

  • Park, Eun-Jin;Yang, Seong-Il;Kim, Young-Kil
    • Annual Conference of KIPS
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    • 2007.05a
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    • pp.707-709
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    • 2007
  • 매일 생성되는 웹 신문에서 독자가 접해보지 못한 단어는 독자의 이해를 돕기 위하여 괄호를 사용한다. 괄호를 사용하여 표기된 웹 신문의 한국어-영어 대역쌍은 특정 기사에는 출현빈도가 낮지만 전체적으로 여러 신문의 기사를 봤을 때, 최소한 한번 이상 출현하게 된다. 즉, 괄호 안의 동일한 영어 용어 두 개 이상의 문장을 최장일치법 알고리즘에 적용하면 한국어 단어 경계를 자동으로 인식할 수 있다. 본 논문에서는 이런 웹 신문의 괄호 표기 특성을 이용하여 한-영 대역어쌍을 추출하는 방법을 제안한다. 웹 신문 기사 43,648 건에서 최대 2,087개의 한-영 대역어를 추출하였다. 3 개의 서로 다른 테스트 그룹으로 실험한 결과 최대 84.2%의 정확도를 보였다.

Using One and One-half Bounded Dichotomous Choice Model to Measure the Economic Benefits of Urban Noise Reduction (1.5경계 양분선택형 모형을 이용한 도시소음 저감의 편익 추정)

  • Yoo, Seung-Hoon
    • Environmental and Resource Economics Review
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    • v.16 no.3
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    • pp.451-483
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    • 2007
  • Recently, the problem of noise has received much attention in the urban environment. This paper attempts to measure the economic benefits of urban noise reduction in the metropolitan area. To this end, the dichotomous choice contingent valuation method is applied. In particular, recently proposed one and one-half bound model that reduces the potential for response bias in the double bound model while maintaining much of its efficiency. We surveyed a randomly selected sample of 800 households in the metropolitan area and asked respondents questions in person-to-person interviews about how they would willing to pay for the noise reduction. Respondents overall accepted the contingent market and were willing to contribute a significant amount (997 to 1,778 won), on average, per household per month. This willingness varies according to individual characteristics such as concerns about noise, dwelling area, and income. The aggregate value of the noise reduction in the sampled metropolitan area amounts to approximately 79.26 to 141.35 billion won per year.

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Phoneme-Boundary-Detection and Phoneme Recognition Research using Neural Network (음소경계검출과 신경망을 이용한 음소인식 연구)

  • 임유두;강민구;최영호
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.11a
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    • pp.224-229
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    • 1999
  • In the field of speech recognition, the research area can be classified into the following two categories: one which is concerned with the development of phoneme-level recognition system, the other with the efficiency of word-level recognition system. The resonable phoneme-level recognition system should detect the phonemic boundaries appropriately and have the improved recognition abilities all the more. The traditional LPC methods detect the phoneme boundaries using Itakura-Saito method which measures the distance between LPC of the standard phoneme data and that of the target speech frame. The MFCC methods which treat spectral transitions as the phonemic boundaries show the lack of adaptability. In this paper, we present new speech recognition system which uses auto-correlation method in the phonemic boundary detection process and the multi-layered Feed-Forward neural network in the recognition process respectively. The proposed system outperforms the traditional methods in the sense of adaptability and another advantage of the proposed system is that feature-extraction part is independent of the recognition process. The results show that frame-unit phonemic recognition system should be possibly implemented.

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Content-based Shot Boundary Detection from MPEG Data using Region Flow and Color Information (영역 흐름 및 칼라 정보를 이용한 MPEG 데이타의 내용 기반 셧 경계 검출)

  • Kang, Hang-Bong
    • Journal of KIISE:Software and Applications
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    • v.27 no.4
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    • pp.402-411
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    • 2000
  • It is an important step in video indexing and retrieval to detect shot boundaries on video data. Some approaches are proposed to detect shot changes by computing color histogram differences or the variances of DCT coefficients. However, these approaches do not consider the content or meaningful features in the image data which are useful in high level video processing. In particular, it is desirable to detect these features from compressed video data because this requires less processing overhead. In this paper, we propose a new method to detect shot boundaries from MPEG data using region flow and color information. First, we reconstruct DC images and compute region flow information and color histogram differences from HSV quantized images. Then, we compute the points at which region flow has discontinuities or color histogram differences are high. Finally, we decide those points as shot boundaries according to our proposed algorithm.

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Optimal Parameter Selection in Edge Strength Hough Transform (경계선 강도 허프 변환에서 최적 파라미터의 결정)

  • Heo, Gyeong-Yong;Woo, Young-Woon;Kim, Kwang-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.5
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    • pp.575-581
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    • 2007
  • Though the Hough transform is a well-known method for detecting analytical shape represented by a number of free parameters, the basic property of the Hough transform, the one-to-many mapping from an image space to a Hough space, causes the innate problem, the sensitivity to noise. To remedy this problem, Edge Strength Hough Transform (ESHT) was proposed and proved to reduce the noise sensitivity. However the performance of ESHT depends on the size of a Hough space and image and some other parameters which should be decided experimentally. In this paper, we derived formulae to decide 2 parameter values; decreasing parameter and broadening parameter, which play an important role in ESHT. Using the derived formulae, 2 parameter values can be decided only with the pre-determined values, the size of a Hough space and an image, which make it possible to decide them automatically. The experiments with different parameter values also support the result.

Regional Boundary Operation for Character Recognition Using Skeleton (골격을 이용한 문자 인식을 위한 지역경계 연산)

  • Yoo, Suk Won
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.4
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    • pp.361-366
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    • 2018
  • For each character constituting learning data, different fonts are added in pixel unit to create MASK, and then pixel values belonging to the MASK are divided into three groups. The experimental data are modified into skeletal forms, and then regional boundary operation is used to create a boundary that distinguishes the background region adjacent to the skeleton of the character from the background of the modified experimental data. Discordance values between the modified experimental data and the MASKs are calculated, and then the MASK with the minimum value is found. This MASK is selected as a finally recognized result for the given experiment data. The recognition algorithm using skeleton of the character and the regional boundary operation can easily extend the learning data set by adding new fonts to the given learning data, and also it is simple to implement, and high character recognition rate can be obtained.

A Study on the Seamline Estimation for Mosaicking of KOMPSAT-3 Images (KOMPSAT-3 영상 모자이킹을 위한 경계선 추정 방법에 대한 연구)

  • Kim, Hyun-ho;Jung, Jaehun;Lee, Donghan;Seo, Doochun
    • Korean Journal of Remote Sensing
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    • v.36 no.6_2
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    • pp.1537-1549
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    • 2020
  • The ground sample distance of KOMPSAT-3 is 0.7 m for panchromatic band, 2.8 m for multi-spectral band, and the swath width of KOMPSAT-3 is 16 km. Therefore, an image of an area wider than the swath width (16 km) cannot be acquired with a single scanning. Thus, after scanning multiple areas in units of swath width, the acquired images should be made into one image. At this time, the necessary algorithm is called image mosaicking or image stitching, and is used for cartography. Mosaic algorithm generally consists of the following 4 steps: (1) Feature extraction and matching, (2) Radiometric balancing, (3) Seamline estimation, and (4) Image blending. In this paper, we have studied an effective seamline estimation method for satellite images. As a result, we can estimate the seamline more accurately than the existing method, and the heterogeneity of the mosaiced images was minimized.

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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A Combined Hough Transform based Edge Detection and Region Growing Method for Region Extraction (영역 추출을 위한 Hough 변환 기반 에지 검출과 영역 확장을 통합한 방법)

  • N.T.B., Nguyen;Kim, Yong-Kwon;Chung, Chin-Wan;Lee, Seok-Lyong;Kim, Deok-Hwan
    • Journal of KIISE:Databases
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    • v.36 no.4
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    • pp.263-279
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    • 2009
  • Shape features in a content-based image retrieval (CBIR) system are divided into two classes: contour-based and region-based. Contour-based shape features are simple but they are not as efficient as region-based shape features. Most systems using the region-based shape feature have to extract the region firs t. The prior works on region-based systems still have shortcomings. They are complex to implement, particularly with respect to region extraction, and do not sufficiently use the spatial relationship between regions in the distance model In this paper, a region extraction method that is the combination of an edge-based method and a region growing method is proposed to accurately extract regions inside an object. Edges inside an object are accurately detected based on the Canny edge detector and the Hough transform. And the modified Integrated Region Matching (IRM) scheme which includes the adjacency relationship of regions is also proposed. It is used to compute the distance between images for the similarity search using shape features. The experimental results show the effectiveness of our region extraction method as well as the modified IRM. In comparison with other works, it is shown that the new region extraction method outperforms others.