利用颜色矩和哈希的实时商业识别

Abhishek Shivadas, J. Gauch
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引用次数: 32

摘要

本文的研究重点是实时商业识别。特别是,我们的目标是在播放的第一秒内正确识别存储在我们的商业数据库中的所有广告。为了实现这一目标,我们使用27个彩色矩来表征每个视频帧的内容。这种表示比大多数颜色直方图表示要紧凑得多,并且对噪声和其他失真不太敏感。我们使用帧级哈希,随后匹配矩向量和视频帧来执行商业识别。散列提供了对数百万视频帧的恒定时间访问,因此这种方法可以实时执行包含数千个商业广告的数据库。在我们对63个广告的数据库进行的实验中,我们在广告播出的前1/2秒内识别广告,达到了96%的召回率,100%的准确率和98%的实用性。
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Real-Time Commercial Recognition Using Color Moments and Hashing
In this paper, our focus is on real-time commercial recognition. In particular, our goal is to correctly identify all commercials that are stored in our commercial database within the first second of their broadcast. To meet this objective, we make use of 27 color moments to characterize the content of every video frame. This representation is much more compact than most color histogram representations, and it less sensitive to noise and other distortion. We use frame-level hashing with subsequent matching of moment vectors and video frames to perform commercial recognition. Hashing provides constant time access to millions of video frames, so this approach can perform in real-time for databases containing thousands of commercials. In our experiments with a database of 63 commercials, we achieved 96% recall, 100% precision, and 98% utility while recognizing commercials within the first 1/2 second of their broadcast.
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