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Color-mood analysis of films based on syntactic and psychological models

机译:基于句法和心理模型的电影色彩情绪分析

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The emergence of peer-to-peer networking and the increase of home PC storage capacity are necessitating efficient scaleable methods for video clustering, recommending and browsing. Based on film theories and psychological models, color-mood is an important factor affecting user emotional preferences. We propose a compact set of features for color-mood analysis and subgenre discrimination. We introduce two color representations for scenes and full films in order to extract the essential moods from the films: a global measure for the color palette and a discriminative measure for the transitions of the moods in the movie. We captured the dominant color ratio and the pace of the movie. Despite the simplicity and efficiency of the features, the classification accuracy was surprisingly good, about 80%, possibly thanks to the prevalence of the color-mood association in feature films.
机译:对等网络的出现以及家用PC存储容量的增加,都需要有效的可伸缩方法来进行视频群集,推荐和浏览。基于电影理论和心理模型,色泽是影响用户情感偏好的重要因素。我们提出了一套紧凑的功能,用于颜色心情分析和亚体别识别。我们为场景和整部电影引入了两种颜色表示形式,以便从电影中提取基本的情绪:对调色板的整体度量和对电影中情绪转变的判别度量。我们捕获了主要的色彩比例和电影的节奏。尽管功能简单且效率高,但分类准确度出乎意料的好,约为80%,这可能归功于故事片中色觉关联的普遍性。

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