Automatic rating of movies using an arousal curve extracted from video features

D. S. Tan, S. See, Thomas James Z. Tiam-Lee
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引用次数: 2

Abstract

This paper discusses the extraction of film structure features from action films to build an arousal curve. The arousal curve is used as training data for building a Hidden Markov Model for predicting the rating of a movie. Evaluation of the model resulted in a 70% accuracy, which shows that there is some form of correlation between the structure of a film and its perceived rating. Interesting similarities were also observed in the arousal curve patterns between different movies in the same classifications.
利用从视频特征中提取的唤醒曲线对电影进行自动评级
本文讨论了从动作电影中提取电影结构特征来构建唤醒曲线的方法。唤醒曲线被用作训练数据,用于建立一个隐马尔可夫模型来预测电影的评级。对模型的评估结果是70%的准确率,这表明电影的结构和它的感知评级之间存在某种形式的相关性。在相同分类的不同电影之间,唤醒曲线模式也有有趣的相似之处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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