Time-constraint boost for TV commercials detection
Time-constraint boost for TV commercials detection
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DOI：
10.1109/icip.2004.1421378
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发表时间：
2004-10
期刊：
影响因子：
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通讯作者：
Tie-Yan Liu;Tao Qin;HongJiang Zhang
中科院分区：
文献类型：
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作者：
Tie-Yan Liu;Tao Qin;HongJiang Zhang
广告检测对于电视广播分析非常重要。但是，视频拍摄的独立分类非常困难，因为很大一部分单个商业镜头看起来很像程序。在本文中，作者提出了一种解决这个问题的新颖方法：通过考虑其时间连贯性来依赖连续的视频拍摄并改善最终分类性能。遵循这个想法，作者讨论了如何将基于多数的窗口和基于少数族裔的合并技术应用于统计分类器的培训和测试过程。结果，提出了一种名为Time-time-constraint Boost的新算法。仿真结果表明，该算法可以提高训练和泛化性能，并导致有希望的广告检测准确性。
Commercials detection is very important for TV broadcast analysis. However, independent classification of video shots is very difficult because a considerable portion of individual commercial shots look very much like the programs. In this paper, the authors proposed a novel way to tackle this problem: to dependently treat successive video shots and improve the final classification performance by considering their temporal coherence. Following this idea, the authors discussed how to apply the majority-based windowing and minority-based merging techniques to the training and test process of statistical classifiers. As a result, a new algorithm named time-constraint boost is proposed. Simulation results show that this algorithm can improve both the training and generalization performance and lead to a promising commercials detection accuracy.