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Determining Computable Scenes in Films and their Structures using Audio-Visual Memory Models

机译:使用视听记忆模型确定电影及其结构中的可计算场景

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In this paper we present novel algorithms for computing scenes and withinscene structures in films. We begin by mapping insights from film-making rules and experimental results form the psychology of audition into a computational scene model. We define a computable secne to be a chunk of audio-visual data that exhibits long-term consistency wiht regard to three propertis: (a) chromaticity (b) lighting (c) ambient sound. Central to the computational model is the notion of a causal, finite-memory viewer model. We segment the audio and video data separatelyh. In each case we determine the degree of correlation of the most recent data in the memory with the past. The respective scene boundaries are ddetermined using local minima and aligned using a nearest neighbor algorithm. We introduce a periodic analysis transform to automatically determine the structure within a scene.
机译:在本文中,我们提出了用于计算电影中场景和场景结构的新颖算法。我们首先将电影制作规则中的见解和实验结果从试听心理学中映射到计算场景模型中。我们将可计算部分定义为视听数据块,该数据块在考虑三种属性的情况下表现出长期一致性:(a)色度(b)照明(c)环境声音。计算模型的核心是因果有限内存查看器模型的概念。我们分别分割音频和视频数据。在每种情况下,我们都确定内存中最新数据与过去的相关程度。使用局部最小值确定各个场景边界,并使用最近邻居算法对齐。我们引入了周期性分析变换来自动确定场景中的结构。

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