• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.38-43
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• 2001

This Paper suggests a new feature for shot detection, using the proposed robust feature from the DC image constructed by DCT DC coefficients in the MPEG video stream, and proposes the characterizing value that reflects the characteristic of kind of video (movie, drama, news, music video etc.). The key frames are pulled out from many frames by using the local minima and maxima of differential of the value. After original frame(not do image) are reconstructed for key frame, indexing process is performed through computing parameters. Key frames that are similar to user's query image are retrieved through computing parameters. It is proved that the proposed methods are better than conventional method from experiments. The retrieval accuracy rate is so high in experiments.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.297-300
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• 2000

본 논문에서는 MPEG 비디오 스트림을 분석하여 DCT DC 계수를 추출하고 이들로 구성된 DC 이미지로부터 제안하는 robust feature를 이용하여 shot을 구하고 각 feature들의 통계적 특성을 이용하여 스트림의 특징에 따라 weight를 부가하여 구해진 characterizing value의 시간변화량을 구한다. 구해진 변화량의 local maxima와 local minima는 MPEG 비디오 스트림에서 각각 가장 특징적인 frame과 평균적인 frame을 나타낸다. 이 순간의 frame을 구함으로서 효과적이고 빠른 시간 내에 key frame을 추출한다. 추출되어진 key frame에 대하여 원영상을 복원한 후, 색인을 위하여 다수의 parameter를 구하고 사용자가 질의한 영상에 대해서 이들 파라메터를 구하여 key frame들과 가장 유사한 대표영상들을 검색한다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.137-143
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• 2003

Key frame extraction has been recognized as one of tile important research issues in video information retrieval. Although progress has been made in key frame extraction, the existing approaches do not evaluate the importance of extracted frame Quantitatively, and Dey are computationally expensive or ineffective. In this Paper, we introduce a new 미해rithm for key frame extraction using shot coverage and distortion. The algorithm finds significant key frames from candidate key frames. When selecting the candidate frames, the coverage rate to the total frames from each frame is computed by using the difference between the adjacent frames in tile shot. The frames within 10$\%$ from the top are selected as the candidates. Then, by comfuting the distortion rate of the candidates against all frames, pick the frames which arc most representative are selected. The performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 13-50$\%$ improvement has been obtained by the proposed algorithm compared to the existing methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.5
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• pp.58-64
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• 2001

Recently many informations are transmitted ,md stored as video data, and they are on the rapid increase because of popularization of high performance computer and internet. In this paper, to retrieve video data, shots are found through analysis of video stream and the method of detection of key frame is studied. Finally users can retrieve the video efficiently. This Paper suggests a new feature that is robust to object movement in a shot and is not sensitive to change of color in boundary detection of shots, and proposes the characterizing value that reflects the characteristic of kind of video (movie, drama, news, music video etc,). The key frames are pulled out from many frames by using the local minima and maxima of differential of the value. After original frame(not de image) are reconstructed for key frame, indexing process is performed through computing parameters. Key frames that arc similar to user's query image arc retrieved through computing parameters. It is proved that the proposed methods are better than conventional method from experiments. The retrieval accuracy rate is so high in experiments.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.539-541
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• 2005

We propose efficient video retrieval scheme which use fast key frame extraction in DCT domain. Our scheme extract key frame using the edge histogram difference which is extracted in compressed domain for I-frames. And the video retrieval is implemented using Hausdorff distance function about edge histogram of key frame. This approach enables fast content-based video retrieval of the compressed video content without decompression process. Experimental results show our scheme is very fast and efficient.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.536-538
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• 2005

As multimedia data and huge-Quantity video data having been increasingly and commonly used, the key frame algorithm, as one of the methods for manipulating these kinds of data, became an important matter and has been studied for many years. But the formerly proposed key frame extraction methods take much processing time or need complex calculations due to decoding processes. In order to solve these problems which the former methods have and to enhance the key frame extraction efficiency, a novel key frame extraction method in compressed domain is proposed in this paper. In this method we get an edge histogram for each I-frame in DCT domain and then extract the key frames by means of histogram difference metric. Experimental results show that our algorithm achieves fast processing speed and high accuracy.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1109-1116
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• 2011

In this paper, we propose a new and fast method for assigning the number of key frames to each shot. At first we segment the entire video sequence into elementary content unit called shots and then the key frame allocation is performed by calculating the accumulated value of AF(activity function). The proposed algorithm is based on the amount of content variation using DC images extracted from compressed video. By assigning the number of key frames to the shot that has the largest value of content function, one key frame is assigned at a time until you run out of given all key frames. The main advantage of our proposed method is that we do not need to use time-exhaustive computations in allocating the key frames over the shot and can perform it fully automatically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1822-1828
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• 2006

A key-frame should be efficiently selected to distinguish bad information from the videos. A previous technique selecting a key-frame mostly consists of the transformation scene-centered. In the case of harmful videos containing the quaility of continuous changes, the technique makes the total rate be reduced by an unnecessary key-frame. This thesis suggests the technique selecting a key-frame, an entry of the distinguishing system by using the quality of changes between the frames. In the experiment of this technique, it was proved that over 90% of the bad information was distinguished by the selected key frame, and also time efficiency was proved by showing 68% of decrement compared to the numbers I-frame. Therefore, This technique makes the system efficient to distinguish bad information, and efficiently can contribute to the distribution of the healthy movie information.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.897-905
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• 2022

Research for video key frame detection has been actively conducted in the fields of computer vision. Recently with the advances on deep learning techniques, performance of key frame detection has been improved, but the various type of video content and complicated background are still a problem for efficient learning. In this paper, we propose a novel method for key frame detection, witch utilizes contrastive learning and memory bank module. The proposed method trains the feature extracting network based on the difference between neighboring frames and frames from separate videos. Founded on the contrastive learning, the method saves and updates key frames in the memory bank, witch efficiently reduce redundancy from the video. Experimental results on video dataset show the effectiveness of the proposed method for key frame detection.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.388-398
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• 2002

Video representation through representative frames (key frames) has been addressed frequently as an efficient way of preserving the whole temporal information of sequence with a considerably smaller amount of data. Such compact video representation is suitable for the purpose of video browsing in limited storage or transmission bandwidth environments. In a case like this, the controllability of the total key frame number (i.e. key frame rate) depending on the storage or bandwidth capacity is an important requirement of a key frame selection method. In this paper, we present a sequential key frame selection method when the number of key frames is given as a constraint. It first selects the desired number of initial key frames and determines non-overlapping initial time intervals that are represented by each key frame. Then, it adjusts the positions of key frames and time intervals by iteration, which minimizes the distortion. Experimental result demonstrates the improved performance of our algorithm over the existing approaches.