• Title/Summary/Keyword: ${\chi}^2$ Histogram

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Video Abstracting Using Scene Change Detection and Shot Clustering for Construction of Efficient Video Database (대용량 비디오 데이터베이스 구축을 위하여 장면전환 검출과 샷 클러스터링을 이용한 비디오 개요 추출)

  • Shin Seong-Yoon;Pyo Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.2 s.40
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    • pp.111-119
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    • 2006
  • Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with $\chi2$ histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

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Video Abstracting Construction of Efficient Video Database (대용량 비디오 데이터베이스 구축을 위한 비디오 개요 추출)

  • Shin Seong-Yoon;Pyo Seong-Bae;Rhee Yang-Won
    • KSCI Review
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    • v.14 no.1
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    • pp.255-264
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    • 2006
  • Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with ${\chi}^2$ histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

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The Efficient Cut Detection Algorithm Using the Weight in News Video Data (뉴스 비디오 데이터에서의 가중치를 이용한 효율적 장면변환 검출 알고리즘)

  • Jeong, Yeong-Eun;Lee, Dong-Seop;Sin, Seong-Yun;Jeon, Geun-Hwan;Bae, Seok-Chan;Lee, Yang-Won
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.2
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    • pp.282-291
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    • 1999
  • In order to construct the News Video Database System, cut detection technique is very important. In general, the color histogram, $\chi$2 histogram or Bin-to-Bin difference(B2B) techniques are mainly using for the scene partitioning. In this paper, we propose the efficient algorithm that is applied the weight in terms of NTSC standard to cut detection. This algorithm is able to reduce the time of acquiring and comparing histogram using by separate calculation of R, G, and B for the color histogram technique. And it also provide the efficient selection method fo threshold value by and use the news videos of KBS, MBC, SBS, CNN and NHK as experimental domains. By the result of experiment, we present the proposed algorithm is more efficient for cut detection than the previous methods, and that the basis for the automatic selection of threshold values.

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News Video Browser (뉴스 비디오 브라우저)

  • Shin, Seong-Yoon;Kang, Oh-Hyung;Kim, Hyung-Jin;Jang, Dai-Hyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.336-337
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    • 2021
  • In this paper, we propose a video browsing service that provides both video content search and video browsing through a real-time user interface on the web. We propose an efficient scene change detection method that combines an RGB color histogram and a 𝛘2 histogram for scene segmentation and key frame extraction of image sequences.

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Extraction of Smoking in Elevator Using χ2 Histogram (χ2히스토그램을 이용한 승강기 내의 흡연 추출)

  • Shin, Seong-Yoon;Kim, Hee-Ae;Jin, Chan-Yong;Park, Sang-Joon;Rhee, Yang-Won;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.119-121
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    • 2013
  • The fact of smoking is prohibited in elevators. Smoking in elevators that contrary to business ethics, and it can be fatal to our children and women. In this paper, people who smoke in elevators is submitted to forensic evidence. Method is to extract the white bar at the mouth, biting people that smoke. ${\chi}^2$ histogram of scene change detection method is extracted.

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Women's Sexual Harassment Incident in The Elevator Using χ2 Histogram (χ2히스토그램을 이용한 승강기 내에서 여성의 성 추행 사건 추출)

  • Shin, Seong-Yoon;Kim, Hee-Ae;Jin, Chan-Yong;Park, Sang-Joon;Rhee, Yang-Won;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.104-106
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    • 2013
  • In crime, sexual harassment is acts arouse sexual shame to the other man by the physical body contact in order to obtain sexual gratification. One of sexual abuse, molestation, means indecent assault. The different point of indecent assault and sexual harassment is 'Harassment' as means of 'assault or intimidation'. In this paper, these incidents of sexual harassment to women in elevators extract by ${\chi}^2$ histogram.

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Extraction of Theft in Elevator Using χ2 Histogram (χ2히스토그램을 이용한 승강기에서 절도 범죄의 추출)

  • Shin, Seong-Yoon;Kim, Hee-Ae;Lee, Sang-Won;Park, Sang-Joon;Rhee, Yang-Won;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.86-88
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    • 2013
  • Theft is secretly steal things of others. And theft tell the person who secretly stealing, bandits, stealing one's things. In modern society, theft is one of the crimes that occur frequently in the elevator. In this paper, theft crime is extracted using a ${\chi}^2$ histogram of scene change detection method. Extracted images are submitted as evidence for the action on the merits the court.

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A Study on Assault and Violence in Elevator Using χ2 Histogram (χ2히스토그램을 이용한 승강기 내에서 폭행 및 폭력사건에 관한 연구)

  • Shin, Seong-Yoon;Kim, Hee-Ae;Jin, Chan-Yong;Park, Sang-Joon;Rhee, Yang-Won;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.109-111
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    • 2013
  • The attack refers to the act deliberately to stimulate an abomination to the people. Of violence, such as physical aggression, direct physical forcing. Assault said to contact the opponent's body with the power to superior opponent. In other words, it is the act of hitting an opponent with the fist. In this paper, the violence and assaults that occur in elevators extracted using a color histogram of scene change detection technique.

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Selectivity Estimation Using Compressed Spatial Histogram (압축된 공간 히스토그램을 이용한 선택율 추정 기법)

  • Chi, Jeong-Hee;Lee, Jin-Yul;Kim, Sang-Ho;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
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    • v.11D no.2
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    • pp.281-292
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    • 2004
  • Selectivity estimation for spatial query is very important process used in finding the most efficient execution plan. Many works have been performed to estimate accurate selectivity. Although they deal with some problems such as false-count, multi-count, they can not get such effects in little memory space. Therefore, we propose a new technique called MW Histogram which is able to compress summary data and get reasonable results and has a flexible structure to react dynamic update. Our method is based on two techniques : (a) MinSkew partitioning algorithm which deal with skewed spatial datasets efficiently (b) Wavelet transformation which compression effect is proven. The experimental results showed that the MW Histogram which the buckets and wavelet coefficients ratio is 0.3 is lower relative error than MinSkew Histogram about 5%-20% queries, demonstrates that MW histogram gets a good selectivity in little memory.

Automatic Threshold-decision Algorithm using the Average and Standard Deviation (평균과 표준편차를 이용한 자동 임계치-결정 알고리즘)

  • Ko, Kyong-Cheol;Rhee, Yang-Won
    • The Journal of Korean Association of Computer Education
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    • v.8 no.6
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    • pp.103-111
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    • 2005
  • This paper presents a novel automated threshold-decision algorithm that uses the mean and standard-deviation values obtained from the difference values of consecutive frames. At first, the calculation of difference values is obtained by the weighted ${\chi}^2$-test algorithm which was modified by joining color histogram to ${\chi}^2$-test algorithm. The weighted ${\chi}^2$-test algorithm can subdivide the difference values by imposing weights according to NTSC standard. In the first step, the proposed automatic threshold-decision algorithm calculates the mean and standard-deviation value from the total difference values, and then subtracts the mean value from the each difference values. In the next step, the same process is performed on the remained difference values, and lastly, the threshold is detected from the mean when the standard deviation has a maximum value. The proposed method is tested on various video sources and, in the experimental results, it is shown that the proposed method efficiently estimates the thresholds and reliably detects scene changes.

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