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Recommendation Method to Make Combined Video from Video Segments

机译:从视频段制作组合视频的推荐方法

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In this paper, we propose a recommendation scheme for media framework, which enables users to make their own videos by writing a story and reusing parts of accumulated videos. To reuse part of videos, we split a video into semantic segments based on an analysis of relations among objects in a video and store the segments with semantics in repository. To create a new video, the user sends queries based on his/her own story, then the framework recommends appropriate video segments for each query. To determine the rank of searched segments, the recommendation engine uses the degree of coincidence between the segment and the query. Also, it uses the degree of similarity between the searched segment and previously selected segment. By doing this, we can recommend a segment, which is consistent with user's intent and harmonized with the other parts of the new video.
机译:在本文中,我们向媒体框架提出了建议计划,这使用户能够通过编写故事和重用累积视频的部分来制作自己的视频。 要重用部分视频,我们将基于对视频中对象之间的关系分析来将视频分成语义段,并在存储库中使用语义存储段。 要创建新视频,用户根据他/她自己的故事发送查询,然后框架为每个查询推荐适当的视频片段。 要确定搜索段的等级,推荐引擎使用段和查询之间的巧合程度。 此外,它使用搜索到的段和先前选择的段之间的相似程度。 通过这样做,我们可以推荐一个段,这与用户的意图一致,并与新视频的其他部分统一。

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