Automatic key-frames extraction to represent a video

Lang, Congyan; Xu, De; Cheng, Wengang; Feng, Songhe

doi:10.1109/icosp.2004.1452769

Cited by 5 publications

(4 citation statements)

References 7 publications

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“…Video segmentation and key frame extraction are the fundamental steps of video analysis and content-based video retrieval [1]- [5]. Key frame extraction is an essential part in video representation and management, providing an appropriate video summarization for video structuring, browsing and retrieval.…”

Section: Introductionmentioning

confidence: 99%

Key frame number assignment measuring content variations

Kim

Kwon

2012

2012 International Conference on ICT Convergence (ICTC)

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Abstract² We propose a new and fast algorithm for assigning the number of key frames to video shots. After the entire video sequence is segmented into elementary content unit called shots and then the key frame number assignment is performed by calculating the accumulated value of CVF(content variation function). The proposed algorithm is based on the amount of content variations 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.

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Section: Introductionmentioning

confidence: 99%

Key frame number assignment measuring content variations

Kim

Kwon

2012

2012 International Conference on ICT Convergence (ICTC)

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“…6, proposed method is superior to Bede Liu's method in respect to dissimilarity measure and a subjective point of view for shot 8 for 5% selected frames. 4. CONCLUSIONS This thesis proposes a new key frame extraction method for content-based video indexing and retrieval.…”

Section: Simulationsmentioning

confidence: 99%

“…Further scene analysis and interpretation can then be performed on such shots. Segmented video sequences can also be used for browsing, in which only one or a few representative frames, i.e., key frames of each shot are displayed [2][3][4][5]. The main goal of the above procedures is to provide the user a compact and easily understandable overview of the complete stored video information.…”

Section: Introductionmentioning

confidence: 99%

New Framework for Automated Extraction of Key Frames from Compressed Video

Kim

Kwon²

2012

Journal of Korea Multimedia Society

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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.

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“…In order to allow the user to efficiently browse, select, and retrieve a desired video part without having to deal directly with GBytes of compressed data, a common first step is to segment the videos into temporal shots, each representing an event or continuous sequence of actions. Next, segmented shots are used for browsing and indexing, in which only one or a few representative frames, i.e., key frames of each shot are displayed [1][2][3][4][5]. To extract key frames from a shot, it is important to properly decide on the number of key frames.…”

Section: Introductionmentioning

confidence: 99%

Key Frame Assignment for Compr essed Video Based on DC Image Activity

Kim¹,

Lee²,

Kwon³

2011

Journal of Korea Multimedia Society

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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.

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Automatic key-frames extraction to represent a video

Cited by 5 publications

References 7 publications

Key frame number assignment measuring content variations

Key frame number assignment measuring content variations

New Framework for Automated Extraction of Key Frames from Compressed Video

Key Frame Assignment for Compr essed Video Based on DC Image Activity

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