Video Retrieval Based on Tracked Features Quantization

Hiroaki Kubo, Julien Pilet, H. Saito, S. Satoh
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Abstract

In this paper, we present an image retrieval method based on feature tracking. Feature tracks are summarized into a compact discreet value and used for video indexing purpose. As opposed to existing space-time features, we do not make any assumption on the motion visible on the indexed videos. As a result, given an example query, our system is able to retrieve related videos from a large database. We evaluated our system with the copy detection benchmark MUSCLE-VCD-2007. We also ran retrieval experiment on hours of TV broadcast.
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基于跟踪特征量化的视频检索
本文提出了一种基于特征跟踪的图像检索方法。特征轨道被总结成一个紧凑的离散值,并用于视频索引目的。与现有的时空特征相反,我们对索引视频中可见的运动不做任何假设。因此,给定一个示例查询,我们的系统能够从大型数据库中检索相关视频。我们用复制检测基准MUSCLE-VCD-2007评估了我们的系统。我们还对电视节目播放时间进行了检索实验。
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