基于生理信号流形表示的观众同步检测:在电影亮点检测中的应用

Michal Muszynski, Theodoros Kostoulas, G. Chanel, Patrizia Lombardo, T. Pun
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引用次数: 10

摘要

电影中的亮点检测是对电影情感理解和隐性标注的挑战。假设观众反应的同步性表明了这些亮点,我们定义了一种能够提取电影亮点的观众之间的同步度量。我们的方法的直观想法是定义(a)一个观众的生理数据在流形上的参数化;(b)观众之间的同步度量作为底层流形局部形状分布之间的Kolmogorov-Smirnov距离。我们使用实验中收集的数据来评估我们的方法,该实验记录了观众在电影放映期间的整个皮肤电活动。我们将我们的方法与基线同步度量进行比较,如相关性、Spearman等级相关性、互信息、Kolmogorov-Smirnov距离。结果表明,该方法可以准确区分高光和非高光场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectators' Synchronization Detection based on Manifold Representation of Physiological Signals: Application to Movie Highlights Detection
Detection of highlights in movies is a challenge for the affective understanding and implicit tagging of films. Under the hypothesis that synchronization of the reaction of spectators indicates such highlights, we define a synchronization measure between spectators that is capable of extracting movie highlights. The intuitive idea of our approach is to define (a) a parameterization of one spectator's physiological data on a manifold; (b) the synchronization measure between spectators as the Kolmogorov-Smirnov distance between local shape distributions of the underlying manifolds. We evaluate our approach using data collected in an experiment where the electro-dermal activity of spectators was recorded during the entire projection of a movie in a cinema. We compare our methodology with baseline synchronization measures, such as correlation, Spearman's rank correlation, mutual information, Kolmogorov-Smirnov distance. Results indicate that the proposed approach allows to accurately distinguish highlight from non-highlight scenes.
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