• ETRI Journal
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• v.18 no.2
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• pp.61-74
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• 1996

We propose two new rate control schemes to improve MPEG-2 rate control in view of visual quality when scene changes happen. Two proposed schemes are characterized by real-time and non real-time improvement to reduce the impact of scene changes. We also propose a new target-bit prediction method using spatial activity of pictures and present a simple and efficient scene change detection scheme using signed difference of mean absolute difference (MAD). Computer simulation results show that the proposed real-time algorithm effectively alleviates visual quality degradation after scene changes. The proposed non real-time algorithm gives maximum 2 dB improvement in peak signal-to-noise ratio (PSNR) at a scene-changed picture, compared with MPEG-2 rate control scheme and it shows better quality than the real-time one.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.115-122
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• 2001

A scene change detection is an important step for video indexing and retrieval. This paper proposes an algorithm by a phased algorithm for fast and accurate detection of abrupt scene changes in an MPEG compressed domain with minimal decoding requirements and computational effort. The proposed method compares two successive I-frames for locating a scene change occurring within the GOP and uses macroblock-coded type information contained in B-frames to detect the exact frame where the scene change occurred. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage. The experiment results demonstrate that the proposed algorithm has better detection performance, such as precision and recall rate, than the existing method using all DC images.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.457-469
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• 2003

In this paper, we have proposed the efficient algorithm that can segment the video scene change using a various statistical characteristics obtained from by applying the wavelet transformation for each frames. Our method firstly extracts the histogram features from low frequency subband of wavelet-transformed image and then uses these features to detect the abrupt scene change. Second, it extracts the edge information from applying the mesh method to the high frequency subband of transformed image. We quantify the extracted edge information as the values of variance characteristic of each pixel and use these values to detect the gradual scene change. And we have also proposed an algorithm how extract the proper key frame from segmented video scene. Experiment results show that the proposed method is both very efficient algorithm in segmenting video frames and also is to become the appropriate key frame extraction method.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.275-280
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• 2002

A new algorithm for gradual scene change detection in MPEG based frame sequences is proposed in this paper. The proposed algorithm is based on the fact that most of gradual curves can be characterized by variance distributions of edge information in the frame sequences. Average edge frame sequences are obtained by performing "sober" edge detection. Features are extracted by comparing variances with those of local blocks in the average edge frames. Those features are further processed by the opening operation to obtain smoothing variance curves. The lowest variance in the local frame sequences is chosen as a gradual detection point. Experimental results show that the proposed method provides 85% precision and 86% recall rate fur gradual scene changes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.549-550
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• 2019

In this paper, we propose a method to detect the scene change using deep learning. To extract feature points, we use a deep neural network and express extracted feature points as 128 dimensional vectors using SIFT descriptor. If it is less than 25%, it is determined that the scene is changed.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.343-350
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• 2002

A scene change detection which involves finding a cut between two consecutive shots is an important step for video indexing and retrieval. This paper proposes an algorithm for fast and accurate detection of abrupt scene changes in an MPEG compressed domain with minimal decoding requirements arid computational effort. The proposed method compares two successive DC images of I-frames for finding the GOP (group of picture) which contain a scene change and uses macroblock-coded type information contained in B-frames to detect the exact frame where the scene change occurred. The experiment results demonstrate that the proposed algorithm has better detection performance, such as precision and recall rate, than the existing method using all DC images. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.129-132
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• 2003

Fixed GOP allocation in MPEG-2 cannot cope with scene change and amount of motion, which results in degradation picture quality. By finding suitable N and M and allocating dynamic GOP, the improvement of picture quality can be achieved. In this paper, N and M are determined by scene change detection and estimation of amount of motion using color histogram per each macroblock. The simulation results show that the average PSNR is improved, especially around the shot boundaries.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.939-947
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• 2019

With the revitalization of the media market, the necessity of compression, searching, editing and copyright protection of videos is increasing. In this paper, we propose a method to detect scene change in all these fields. We propose a pre-processing, feature point extraction using SIFT, and matching algorithm for detecting the same scene change even if distortions such as resolution change, subtitle insertion, compression, and flip are added in the distribution process. Also, it is applied to filtering technology and it is confirmed that it is effective for all transformations other than considering transform.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.534-542
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• 1999

A sell-designed rate control strategy can improve overall picture quality for video transmission over a constant bit rate channel and the rate control method is not a normative part of MPEG-video standard, the performance of MPEG video codec can be quite different depends on how to implement the rate control scheme. The rate control scheme proposed in MPEG show good results when scene changes is not occurred. But it has weakness that it does not properly handle scene-changed pictures. Therefore picture quality after scene change is deteriorated, and possibility of overflow occurrence becomes high. In this paper, a new method for detection of scene change occurrence using local variance and a new determination scheme for adaptive quantization parameter, mqunt, which can consider local characteristic of an image by using previously computed the local variance from the scene change detection part are proposed. IN addition, and adaptive rate control scheme which can handles scene changed picture very efficiently by scene-changed picture is proposed. Computer simulations are performed to verify the performance of the proposed algorithm. The suggested detection algorithm precisely detected scene change. And the proposed rate control scheme shows better rate control performance as compared with that of the conventional MPEG scheme.

• 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.