期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2014
卷号：4
期号：4
页码：593-602
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：The significant development of multimedia and dijital video production in recent years has led to the mass production of personal and commerical video archives.Therefore, the need for efficient tools and methods of accessing video content and information rapidly is significantly increasing. Video summarization is the removal of visual redundancy and repetitive video frames,and obtaining a short summary of the whole video so that the summary obtained effectively reflects the whole video content. Examples of these summarizations in recent years include STIMO and VSUMM.According to users' comments, in the mentioned methods, the summarization has a high rate of error in a full report of summarization and a low accuracy in non-repetitive frames production, as well as a high computation time.In this paper.in order to solve these problems,we developed a system which modeled users' and supervisors' comments.We used a fuzzy based incremental clustering by which the selection and deselection of frames are done based on fuzzy rules. The extracted rules were determined based on users' comments on the video summarization.Finally, we performed our proposed method on the video clips used in the previous methodes.Produced summaries were evaluated by a qualitative method to minimize human interferences.The results obtained indicate the high accuracy of summarization and the less computation time.DOI:http://dx.doi.org/10.11591/ijece.v4i4.5836
其他摘要：The significant development of multimedia and dijital video production in recent years has led to the mass production of personal and commerical video archives.Therefore, the need for efficient tools and methods of accessing video content and information rapidly is significantly increasing. Video summarization is the removal of visual redundancy and repetitive video frames,and obtaining a short summary of the whole video so that the summary obtained effectively reflects the whole video content. Examples of these summarizations in recent years include STIMO and VSUMM.According to users' comments, in the mentioned methods, the summarization has a high rate of error in a full report of summarization and a low accuracy in non-repetitive frames production, as well as a high computation time.In this paper.in order to solve these problems,we developed a system which modeled users' and supervisors' comments.We used a fuzzy based incremental clustering by which the selection and deselection of frames are done based on fuzzy rules. The extracted rules were determined based on users' comments on the video summarization.Finally, we performed our proposed method on the video clips used in the previous methodes.Produced summaries were evaluated by a qualitative method to minimize human interferences.The results obtained indicate the high accuracy of summarization and the less computation time. DOI: http://dx.doi.org/10.11591/ijece.v4i4.5836
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