• Title/Summary/Keyword: Scene change Detection

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Fast Scene Change Detection Using Macro Block Information and Spatio-temporal Histogram (매크로 블록 정보와 시공간 히스토그램을 이용한 빠른 장면전환검출)

  • Jin, Ju-Kyong;Cho, Ju-Hee;Jeong, Jae-Hyup;Jeong, Dong-Suk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.141-148
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    • 2011
  • Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.

Detection of Assault and Violence Using Color Histogram in Elevator (컬러히스토그램을 이용한 승강기에서 폭행 및 폭력 사건의 추출)

  • Shin, Seong-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.12
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    • pp.95-100
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    • 2012
  • In this paper, we see the means for the assault, the type of unlawful exercise of power. Also, we see the violence, the physical exercise accompanying with assault. Now, it has caused numerous crimes in elevators. This paper is to present a way to extract the violence and assault that occurred in elevators. Key frame was extract by color histogram method, one of the ways to scene change detection techniques. Extracted key frames are key frames of a scene containing a forensic crime scene video. Also, the key frames of the scene should be submitted to the forensic evidence.

Detection of Fast Scene Changes Using a Statistical Technique (영상의 통계적 특성을 이용한 급격한 장면전화 검출 알고리즘)

  • 곽대호;박성준;이건호;최유태;송문호
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.151-154
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    • 2000
  • We propose a statically motivated scene change detection algorithm. As the difference between the neighboring frames will generate peaks at scene boundaries, the problem of detecting fast scene changes is equivalent to detecting peaks in a given sequence. In this paper, the peak detection is performed via several statistics, namely the sample means and variances. For eliminating flash lights as well as detecting fast scene changes within a small number of frames, we have opted to use a two-stage process for computing the necessary statistics. The results indicate superiority of necessary statistics. The results indicate superiority of the proposed algorithm over the previously reported algorithm.

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Feature Extraction for Scene Change Detection in an MPEG Video Sequence (장면 전환 검출을 위한 MPEG 비디오 시퀀스로부터 특징 요소 추출)

  • 최윤석;곽영경;고성제
    • Journal of Broadcast Engineering
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    • v.3 no.2
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    • pp.127-137
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    • 1998
  • In this paper, we propose the method of extracting edge information from MPEG video sequences for the detection of scene changes. In a the proposed method, five significant AC coefficients of each MPEG block are utilized to obtain edge images from the MPEG video. AC edge images obtained by the proposed scheme not only produce better object boundary information than conventional methods using only DC coefficients, but also can reduce the boundary effects produced by DC-based. Since the AC edge image contains the content information of each frame, it can be effectively utilized for the detection of scene change as well as the content-based video query. Experimental results show that the proposed method can be effectively utilized for the detection of scene changes.

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Change Detection in Land-Cover Pattern Using Region Growing Segmentation and Fuzzy Classification

  • Lee Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.21 no.1
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    • pp.83-89
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    • 2005
  • This study utilized a spatial region growing segmentation and a classification using fuzzy membership vectors to detect the changes in the images observed at different dates. Consider two co-registered images of the same scene, and one image is supposed to have the class map of the scene at the observation time. The method performs the unsupervised segmentation and the fuzzy classification for the other image, and then detects the changes in the scene by examining the changes in the fuzzy membership vectors of the segmented regions in the classification procedure. The algorithm was evaluated with simulated images and then applied to a real scene of the Korean Peninsula using the KOMPSAT-l EOC images. In the expertments, the proposed method showed a great performance for detecting changes in land-cover.

Enhancement of Sleep Quality Using Scene Change Detection of Color Histogram (컬러히스토그램의 장면 전환 검출을 이용한 수면의 질 향상)

  • Shin, Seong-Yoon;Shin, Kwang-Seong;Lee, Hyun-Chang;Rhee, Yang-Won
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2011.06a
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    • pp.49-50
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    • 2011
  • In this paper we collect data concerning sleep environments in a bedroom and analyze the relationship between the collected condition data and sleep. In addition, this paper detects scene changes from the subjects in a sleeping state and presents the physical conditions, reactions during sleep, and physical sensations and stimuli. To detect scene changes in image sequences, we used color histogram for the difference between the preceding frame and the current frame. In addition, to extract the tossing and turning for different situations, the subjects were instructed to enter the level of fatigue, the level of drinking, and the level of stomach emptiness.

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Improving Histogram Scene Change Detection Method Using Motion Vector (움직임 벡터를 이용한 히스토그램 장면 전환 검출 기법의 개선)

  • 한영욱;정성일;김성재;이시영;김승호
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.410-412
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    • 1999
  • 히스토그램 장면 전환 검출(histogram scene change detection) 기법은 입력 영상 내에 카메라 동작(camera operation)이 발생한 부분을 컷(cut)으로 나누는 문제점이 있다. 본 논문에서는 이러한 문제점을 해결하기 위해 프레임 사이의 움직임 벡터를 측정하여 카메라 동작이 일어났는지를 판단하고, 이를 이용하여 잘못된 컷의 인식을 막는다. 카메라 동작이 발생하는 샷의 경제는 컷이 될 수 없으므로, 이외의 샷에 대해 컬러 히스토그램 교집합(color histogram intersection)을 구해서 장면 전환 여부를 판단한다. 제안된 기법은 기존의 히스토그램 장면 전환 검출 기법보다 프리시젼(Precision) 면에서 성능 향상을 보였다.

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Scene change detection and simulation tool in video sequence (비디오 시퀀스에서 장면 전환 검출과 시뮬레이터의 구성)

  • 김성주;강응관;최종수
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1998.06a
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    • pp.139-142
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    • 1998
  • 장면 전환 검출(scene change detection)을 영상 정보의 인덱싱 및 검색을 위한 전처리로서, 전체 검색 시스템의 성능을 좌우하는 중요한 기술로 현재 많은 연구가 진행되고 있다. 본 논문에서는 MPEG 표준으로 압축된 동영상으로부터 얻은 DC 이미지를 이용한 장면 전환 검출 및 대표 프레임 검출에 대한 방법을 제안하고 이를 위한 시뮬레이터의 개발과 그에 대한 성능을 평가한다.

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Scene Change Detection In the Hard Disk Drive Embedded Digital Satellite Receiver for Video Indexing (하드디스크를 내장한 디지털 위성방송수신기에서 비디오 인덱스를 위한 장면 전환 검출)

  • 성영경;최윤희;최태선
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.259-262
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    • 2002
  • In this paper, we present a hard disk drive embedded digital satellite receiver with scene change detection for video indexing. This receiver can store, retrieve and classify the broadcast data by implementing an interface between the conventional digital satellite receiver and digital storage media. Using this system, user can obtain more information for efficient video retrieval.

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Scene Change Detection Using MPEG Bitstream and Sectionally Decoded Video (MPEG 비트스트림과 구간 복호 영상을 사용한 장면 전환 검출)

  • 나윤정;하명환;이상길
    • Journal of Broadcast Engineering
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    • v.4 no.2
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    • pp.119-126
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    • 1999
  • We proposed an algorithm which detects scene changes in video with speediness and accuracy. It is a two-step approach. In the first step, we decide potential scene change segments using the compressed domain data extracted by temporal sampling of MPEG compressed video. In the second step, we determine the exact scene change positions using the pixel values of each frame in those segments by means of combining the intensity and edge changes. In addition we discuss the method to remove false detection generated from camera flash. Integrating the above methods, we introduce a structure that can detect scene changes speedily and accurately.

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