Abstract

Video represented by a large number of frames synchronized with audio making video saving requires more storage, it's delivery slower, and computation cost expensive. Video summarization provides entire video information in minimum amount of time. This paper proposes static and dynamic video summarizationmethods. The proposed static video summarization method includes several steps which are extracting frames from video, keyframes selection, feature extraction and description, and matching feature descriptor with bag of visual words, and finally save frames when features matched. The proposed dynamic video summarizationmethod includes in general extracting audio from video, calculating audio features using the average of samples in windows and find the highest average which reflects portion of video with loudest sound. The experimental results for the proposed static video summarization show that there is no redundancy between selected representative keyframes and the subjective evaluation results ensure the importance of the selected keyframes. While the experimental results for the proposed static video summarization show that all the segments of goals have been extracted to provide video summary. Static and dynamic video summarization methods done to football or soccer video type.

Highlights

  • IntroductionVideo is advanced multimedia that has been enabled by the availability of internet in the communication field

  • Video can be defined as a sequence of frames and sounds that makes up the video

  • This paper organizes as follows: section 2 presents some of the related works; section 3 presents methods used for video and image segmentation; section 4 presents Scale Invariant Feature Transform (SIFT) features extraction and description method; section 5 presents Bag of Visual Words (BoVW) method; section 6 presents video summarization concept; section 7 presents the proposed video summarization methods; section 8 presents video summary evaluation approaches; section 9 presents experimental results; section 10 presents conclusion

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Summary

Introduction

Video is advanced multimedia that has been enabled by the availability of internet in the communication field. Increasing the use of internet videos has brought the need to summarize the videos to a smaller size to make video available for using in multiple networks at low cost. To summarize any type of video, researchers have relied on visual features contained in frames [2]. This paper organizes as follows: section 2 presents some of the related works; section 3 presents methods used for video and image segmentation; section 4 presents SIFT features extraction and description method; section 5 presents Bag of Visual Words (BoVW) method; section 6 presents video summarization concept; section 7 presents the proposed video summarization methods; section 8 presents video summary evaluation approaches; section 9 presents experimental results; section 10 presents conclusion

Relate work
OTSU’s Method
Normalization
Video summary evaluation
Experimental Results
Summary Time
10. Conclusion
Full Text
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