• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.353-360
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• 2004

The study on scene change detection in the compressed MPEG videos has been done by various approaches. However, most of these approacher accomplished scene change detection by carrying out decoding processes and then by comparing pixels with pixels. This approach it not suitable for real time applications owing to much computing time of decoding processes. Recently, the study on scene change detection algorithms using only information of compressed domain is becoming Increasingly important. In this paper, we propose a sequential access method as an efficient scene change detection algorithm in the compressed domain. According to the type of pictures in the compressed MPEG video streams (divided in I-blocks and each I-block into P-blocks), the proposed algorithm provides effective scene change detection by applying sequential access and block by block mechanism. The proposed sequential access method provides fast and accurate detection operation by reducing checking procedures of unnecessary pictures due to molt of operations in compressed domain and checking by block units. Also, this approach uses optimal algorithm to provide fast and accurate detection operation.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.27-40
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• 2001

The purpose of this study is to test a multiple change point in the regression model with the passage of time, using the estimated residual variance figure suggested by Gasser, Sroka and Jennen - Steinmez (GSJS). As a result of the simulation, it is showed that there is a jump change of the estimated residual variance figure at that time of change point. The way to analyse a intuitive multiple change point through graphics is more effective and accurate than any other existing ways.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.514-522
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• 2003

Contrary to the previous methods, in this paper, we propose an enhanced shot change detection method using multiple features and binary decision tree. The previous methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using multiple features, which are supplementary each other, rather than using single feature. In order to classify the shot changes, we use binary classification tree. According to this classification result, we extract important features among the multiple features and obtain threshold value for each feature. We also perform the cross-validation and droop-case to verify the performance of our method. From an experimental result, it was revealed that the EI of our method performed average of 2% better than that of the conventional shot change detection methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1414-1424
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• 2004

In this paper, an algorithm using wavelet transform for detecting a cut that is a radical scene transition point, and fade and dissolve that are gradual scene transition points is proposed. The conventional methods using wavelet transform for this purpose is using features in both spatial and frequency domain. But in the proposed algorithm, the color space of an input image is converted to YUV and then luminance component Y is transformed in frequency domain using 2-level lifting. Then, the histogram of only low frequency subband that may contain some spatial domain features is compared with the previous one. Edges obtained from other higher bands can be divided into global, semi-global and local regions and the histogram of each edge region is compared. The experimental results show the performance improvement of about 17% in recall and 18% in precision and also show a good performance in fade and dissolve detection.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.877-885
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• 2004

In this paper, we propose an enhancement shot change detection method using the neural net and the robust feature selection out of multiple features. The previous shot change detection methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using robust features, which are supplementary each other, rather than using single feature. In this paper, we use the typical CART (classification and regression tree) of data mining method to select the robust features, and the backpropagation neural net to determine the threshold of the each selected features. And to evaluation the performance of the robust feature selection, we compare the proposed method to the PCA(principal component analysis) method of the typical feature selection. According to the experimental result. it was revealed that the performance of our method had better that than the PCA method.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.289-292
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• 2002

동영상 검색 시스템은 사용자가 전체 동영상 정보를 한눈에 파악할 수 있어야 한다. 필요한 경우 원하는 지점부터 직접 재생할 수 있도록 해야 한다. 이에 대한 많은 연구가 수행되고 있다. 그러나 데이터를 처리하는데 시간이 오래 걸리는 등의 몇가지 문제점이 있다. 따라서 본 논문은 내용기반 색인에 기초가 될 동영상의 장면전환점 검출에 관한 효과적인 방법을 제안하였다. 제안된 방법은 프레임의 수평방향, 수직방향 또는 대각선 방향으로 나누어 일정한 픽셀 값을 추출하여 정지영상으로 변환하였다. 각각의 프레임에서 추출한 픽셀의 칼라값을 저장하고 MSE(Mean Square Error)를 이용하여 일정한 임계값에 도달하지 못한 프레임을 장면전환점으로 검출하였다. 검출된 장면전환점을 이용하여 변화된 프레임의 장면전환을 검색하는 시스템을 구현하였다.

• The KIPS Transactions:PartB
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• v.8B no.4
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• pp.403-410
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• 2001

물체의 형상을 부호화하기 위한 베이스라인기반 기법을 개선하였다. 베이스라인 기반 기법은 2차원인 물체의 형상 데이터를 전환점(turning point)과 기준선(Baseline)으로 부터의 거리값으로 부호화하는 방식이다. 즉, 가로나 세로의 한 방향의 거리 값과 다른 방향의 전환점을 부호화하는 방식이다. 본 논문에서는 기존의 베이스라인 기반 기법의 성능을 개선하기 위한 방법을 제안하였다. 첫 번째 방법은 허용 왜곡과 비트율을 판단하여 가로나 세로로 기준점의 방향을 변화시킴으로서 부호화해야하는 점들과 전환점들의 개수를 감소시켜서 압축률을 높이는 것이다. 두 번째 방법은 기존의 부표본화에서 사용된 왜곡을 판단보다 더 세밀하게 판단하여 더 많은 종류의 부표본화를 가능케 함으로써 압축률을 높이는 방법이다. 제안하는 방법이 기존의 베이스라인 기반 부호화와 MPEG-4에서 채택하고 있는 CAE(Context-based Arithmetic Encoding)와 비교해 보았을 때 보다 우수한 성능을 보임을 모의실험을 통해 확인하였다.

• 중국학논총
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• no.66
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• pp.161-188
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• 2020

The purpose of this paper is to analyze the debate on the Lewisian turning point in China. Despite the heated debate and accumulating research results both inside and outside China, the results showed a very complex spectrum. Different results were presented depending on which criteria the researcher selected, which analytical tools were used, and which data were utilized. Territory of China is vast, and the differences in economic basement and development stages between regions are not only severe, but also the economic gap among areas in a region is big. Therefore, it is difficult to have a significant meaning in analyzing the Lewisian Turning Point China as a whole. In addition, China's industrial production and labor force structure remain very unbalanced. This can be said to be due to the fact that the allocation and relocation of labor force according to the stage of economic development has not been achieved reasonably, and so it confuses the task of determining whether the Lewis Turning Point has arrived of not.

• Nuclear industry
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• v.11 no.7 s.101
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• pp.80-89
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• 1991

• KLA journal
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• v.17 no.2
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• pp.2-2
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• 1976