• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1199-1203
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• 2012

This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.829-836
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• 2018

This study attempts to detect a shot boundary in films(or dramas) based on the length of a sequence. As films or dramas use scene change effects a lot, the issues regarding the effects are more diverse than those used in surveillance cameras, sports videos, medical care and security. Visual techniques used in films are focused on the human sense of aesthetic therefore, it is difficult to solve the errors in shot boundary detection with the method employed in surveillance cameras. In order to define the errors arisen from the scene change effects between the images and resolve those issues, the mixed algorithm based upon color histogram, edge histogram, and optical flow was implemented. The shot boundary data from this study will be used when analysing the configuration of meaningful shots in sequences in the future.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1431-1433
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• 1987

To transmit the image data at low rate, motion compensated(MC) hybrid coding scheme is used generally. In this scheme since coder performance could be decreased when scene change happens, another prediction method must be employed. In this paper we present two prediction methods. One is using the mean of neighboring block which was already transmitted. The others is estimating the current block with the neighboring blocks. When the proposed methods are applied to the conventional Me hybrid coding scheme, it is found that SNR gain of 7 dB is achieved and bit rate can be also reduced above 30%.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.75-82
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• 2002

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 χ2 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.259-262
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• 2012

In this paper, we propose a new fast algorithm for effective scene change detection. The proposed algorithm exploits Otsu threshold matching technique, which was proposed earlier. In this method, the current and the reference frames are divided into square blocks of particular size. After doing so, the pixel histogram of each block is generated. According to Otsu method, every histogram distribution is assumed to be bimodal, i.e. pixel distribution can be divided into two groups, based on within-group variance value. The pixel value that minimizes the within-group variance is said to be Otsu threshold. After Otsu threshold is found, the same procedure is performed at the reference frame. If the difference between Otsu threshold of a block in the current frame and co-located block in the reference frame is larger than predefined threshold, then a scene change between those two blocks is detected.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1044-1049
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• 2000

In detection of a scene change of the moving pictures which has massive information capacity, the temporal sampling method has faster searching speed than the sequential searching method for the whole moving pictures, yet employed searching algorithm and detection interval greatly affect searching time and searching precision. In this study, the whole moving pictures were primarily retrieved by the temporal sampling method. When there exist a scene change within the sampling interval, we suggested a fast searching algorithm using binary searching and derived an equation formula to determine optimal primary retrieval which can minimize computation, and showed the result of the experiment on MPEG moving pictures. The result of the experiment shows that the searching speed of the suggested algorithm is maximum 13 times faster than the one of he sequential searching method.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.265-268
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• 2001

In content-based video data retrieval, the representative-frame is usually used. To do that, the skill of detection for scene change is needed. Generally the color histogram comparison is used, but sensitive to light variation and tends to miss the scene change of similar color histogram. This paper shows how to use both color histogram comparison and entropy to prevent the false-positive of scene change occurred by light variation. At the experiments, il is more powerful to light variation to use both color histogram comparison entropy than to use only color histogram comparison.

• KSCI Review
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• v.15 no.1
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• pp.203-207
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• 2007

본 논문에서는 비디오의 분할을 위하여 먼저 기존에 제안되었던 차이 값 추출방법들의 단점들을 극복하고 장점을 최대한 활용할 수 있으며 급진적 장면전환부터 점진적 장면전환까지 모두 예측할 수 있는 강건하고 복합적인 차이 값 추출방법에 대해서 제안한다. 이 방법은 지역적 $X^2$-테스트로서 기존의 컬러 히스토그램과 $X^2$-테스트를 결합한 방법이다. 본 논문을 위하여 기존의 히스토그램 기반 알고리즘과 비교하여 좋은 성능을 보여주는 $X^2$-테스트를 변형하였고, 컬러 값의 세분화 작업에 따른 검출효과를 높이기 위하여 명암도 등급에 따른 가중치를 적용한 지역적 $X^2$-테스트를 이용하였다. 이 방법은 복잡하고 다양한 시세계의 영상 변화를 가장 일반적이고 표준화된 방법으로 분석하고 분할하며 표현할 수 있는 방법이다. 기존의 $X^2$-테스트와 제안된 지역적 $X^2$-테스트 방법의 비교는 실험을 통해 입증되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.951-957
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• 2002

When retrieving voluminous capacity of video image data, it is necessary to provide synopsized frame lists of video image data for indexing and replaying at the exact point where the user want to retrieve. We apply Mean Squared Error method to extract certain pixel value from diagonal direction of a frame. The RGB value of a pixel extracted from each frame is saved in a matrix form, and this frame is retrievedas a scene change point if the compared value of two points met the certain condition. Also implement the algorithm and provide a way to seize entire structure of video image and the point of scene changes. finally, we analyze and prove that our method has better performance compared with the others.