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

机译:我记得看到这个视频:视频集合中的图像驱动搜索

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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 yes/no 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视频数据中的图像驱动射击检索技术。具体地,给定查询映像,我们的方法可以有效地选择包含该图像的视频段。视频首先分为镜头。使用嵌入式隐马尔可夫模型(EHMM)描述每次拍摄。 EHMM在该拍摄的帧的GIST形描述符上培训。训练有素的ehmm计算查询图像属于镜头的可能性。每个EHMM培训支持向量机分类器。如果通过其EHMM产生的似然值,该分类器提供了是/否决定。鉴于来自一个或多个视频的拍摄模型集合,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确定图像是否属于视频。所提出的技术在逼真的数据集上进行评估。

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