• 한국멀티미디어학회논문지
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• 제15권6호
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• pp.693-700
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• 2012

The effective extraction of key frames from a video stream is an essential task for summarizing and representing the content of a video. Accordingly, this paper proposes a new and fast method for extracting key frames from a compressed video. In the proposed approach, after the entire video sequence has been segmented into elementary content units, called shots, key frame extraction is performed by first assigning the number of key frames to each shot, and then distributing the key frames over the shot using a probabilistic approach to locate the optimal position of the key frames. The main advantage of the proposed method is that no time-consuming computations are needed for distributing the key frames within the shots and the procedure for key frame extraction is completely automatic. Furthermore, the set of key frames is independent of any subjective thresholds or manually set parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4533-4551
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• 2014

The effective extraction of key frames from a video stream is an essential task for summarizing and representing the content of a video. Accordingly, this paper proposes a new and fast method for extracting key frames from a compressed video. In the proposed approach, after the entire video sequence has been segmented into elementary content units, called shots, key frame extraction is performed by first assigning the number of key frames to each shot, and then distributing the key frames over the shot using a probabilistic approach to locate the optimal position of the key frames. Moreover, we implement our proposed framework in Android to confirm the validity, availability and usefulness. The main advantage of the proposed method is that no time-consuming computations are needed for distributing the key frames within the shots and the procedure for key frame extraction is completely automatic. Furthermore, the set of key frames is independent of any subjective thresholds or manually set parameters.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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• pp.213-216
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• 2001

Key frame extraction is an important method of summarizing a long video. This paper propose a technique to automatically extract several key frames representative of its content from video. We use the color layout descriptor to select key frames from video. For selection of key frames, we calculate similarity of color layout features extracted from video, and extract key frames using similarity. An important aspect of our algorithm is that does not assume a fixed number of key frames per video; instead, it selects the number of appropriate key frames of summarizing a long video Experimental results show that our method using color layout descriptor can successfully select several key frames from a video, and we confirmed that the processing speed for extracting key frames from video is considerably fast.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(3)
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• pp.137-140
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• 2000

In this paper, we propose as new algorithm for the selection of key frames in a given video. For the selected key frames to be well defined, the selected key frames need to spread out on the whole temporal domain of the given video and guaranteed not to be duplicate. For this purpose, we take the first frame of each shot of the video as the candidate key frame to represent the video. To reduce the overall processing time, we eliminate some candidate key frames which are visually indistinct in the histogram difference. The key frames are then selected using a clustering processing based on the singly linked hierarchical tree. To make the selected key frames be distributed evenly on the whole video, the deviation and time difference between the selected key frames are used. The simulation results demonstrate that our method provides the better performance compared with previous methods.

• 전자공학회논문지CI
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• 제40권3호
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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.

• 한국멀티미디어학회논문지
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• 제14권9호
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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.

• 한국정보과학회논문지:소프트웨어및응용
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• 제27권5호
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• pp.510-520
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• 2000

내용 기반의 비디오 인덱싱 및 검색을 위해서는 비디오 데이타를 셧(shot)으로 분할하고, 또 각 셧을 나타내는 대표 프레임을 선택하는 것이 필요하다. 하지만, 대표 프레임을 선택하는 것은 주관적이어서 일관되게 자동적으로 대표 프레임을 선택하는 것은 쉬운 문제가 아니다. 본 논문에서는 각 프레임에서의 영역을 바탕으로한 컨텐트 정보 및 시간 축 상의 변화를 이용하여 계층적으로 대표 프레임을 선택하는 방법을 제안한다. 먼저, 비디오 셧에서 카메라 모션을 검출하여 이에 따라 비디오 셧을 분류한다. 다음, 분류된 비디오 셧에 컨텐트의 중요도를 계산하기 위한 퍼지 규칙을 적용하여 대표 프레임을 선택한다. 끝으로, 선택되는 대표 프레임의 수는 브라우징 상세도(detailness)에 따라 계층적으로 선택되게끔 한다.

• International Journal of Contents
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• 제12권1호
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• pp.1-5
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• 2016

To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.179-182
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• 2001

In this paper. a key frame extraction algorithm for browsing and searching the summary of a video is proposed. Toward this end, important frames representing a shot are selected according to the correlations among frames. by using the Fourier descriptor which is useful for the shot boundary detection. To quantitatively evaluate the importance of selected frames. a new measure based on correlation coefficients of frames is proposed. If there are several frames with a same importance. another criteria is introduced to break the tie. by computing the partial moment of subframes including each candidate key frame so that the distortion rate is minimized Since a key frame extraction algorithm can be evaluated subjectively. the performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 20% improvement has been obtained by the proposed algorithm compared to existing methods.

• 대한전자공학회논문지SP
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• 제39권4호
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• pp.388-398
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• 2002

주요 화면은 보다 적은 양의 데이터를 사용해서 비디오가 갖는 시각적 내용물의 변화량을 효과적으로 표현하기 위해 많이 사용된다. 이와 같은 비디오 표현 방식은 대역폭이나 저장 용량이 제한된 상황에 적합하다. 이 경우 대역폭이나 저장 용량에 따라 주요 화면의 개수를 조절하는 능력은 주요 화면 선택 기법의 중요한 필요 사항 중 하나다. 본 논문에서는 주요 화면의 개수가 제한 조건일 때 순차적인 주요 화면을 찾는 방법을 제안한다. 제안하는 기법은 먼저 원하는 개수의 초기 주요 화면을 미리 선택하고 이들이 대표하는 서로 중복되지 않는 시구간을 정한 후 반복 과정을 통해 주요 화면의 위치와 시구간의 크기를 조절하면서 왜곡 값이 최소가 되도록 주요 화면과 시구간을 찾는다. 실험 결과 제안하는 방법이 선택하는 주요 화면들은 율-왜곡 관점에서 기존의 방법보다 우수하고 인간의 시각 인지와도 일치함을 알 수 있었다.