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I Remember Seeing This Video: Image Driven Search in Video Collections

机译:我记得看过该视频:视频收藏集中的图像驱动搜索

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摘要

We present a novel technique for image driven shot retrieval in video data. Specifically, given a query image, our method can efficiently pick the video segment containing that image. Video is first divided into shots. Each shot is described using an embedded hidden Markov model (EHMM). The EHMM is trained on GIST-like descriptors of frames in that shot. The trained EHMM computes the likelihood that a query image belongs to the shot. A Support Vector Machine classifier is trained for each EHMM. The classifier provides a yeso decision given the likelihood value produced by its EHMM. Given a collection of shot models from one or more videos, the proposed technique can efficiently decide whether or not an image belongs to a video by identifying the shot most likely to contain that image. The proposed technique is evaluated on a realistic dataset.
机译:我们提出了一种新颖的技术,用于在视频数据中进行图像驱动的镜头检索。具体来说,给定查询图像,我们的方法可以有效地选择包含该图像的视频片段。视频首先分为镜头。使用嵌入的隐马尔可夫模型(EHMM)描述每个镜头。 EHMM使用该镜头中类似GIST的帧描述符进行训练。训练有素的EHMM计算查询图像属于镜头的可能性。支持向量机分类器针对每个EHMM进行训练。给定其EHMM产生的似然值,分类器提供是/否决定。给定一个或多个视频的镜头模型集合,所提出的技术可以通过识别最有可能包含该图像的镜头来有效地决定图像是否属于视频。所提出的技术在现实的数据集上进行了评估。

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