Study on Controlling Emotion of a Multimedia Viewer Based on Interactive Evolutionary Computation and Physiological Analysis

我们在2005-2007财年分三步进行了这项研究。在第一步“提取可能影响生理反应的可能电影特征“中，我们首先从多种电影中剪切60个20秒的场景，提取78个物理电影特征。其次，我们构建了一个二维的心理空间，称为情感空间，（张力-松弛）轴和第二步，“提取电影特征和生理反应之间的关系，“我们首先制作了一个抽象的实验电影场景，其中一个特征有20个不同的变量，这些变量在30个特征中显示出最高的相关性。由于电影语境即故事对人的情感有着深刻的影响，所以为了避免这种影响，我们采用了抽象的电影场景。其次，我们通过显示抽象的电影来测量生理数据。测量数据为两侧点和两侧背侧的EEG、ECG、出汗率、血压水平和手指脉搏量。然而，受试者之间测量数据的差异大于物理电影特征值的差异，我们尚未发现电影特征与生理反应之间的显著关系。第三步，”使用扩展交互式进化计算（IEC）建立驾驶情绪，“我们的目标是建立一种优化电影特征的技术，以使电影观众的生理状况达到给定的目标条件。由于我们还没有找到在第二步中确实驱动人体生理的电影特征，我们专注于改进IEC技术。我们所做的是将IEC与进化多目标优化相结合，引入粒子群优化代替进化计算，引入IEC用户评价模型等。

We conducted this research with three steps in 2005-2007 fiscal years.In the first step, “extracting possible movie features that may influence physiological responses, “we firstly cut 60 scenes of 20 seconds from several varieties of movies and extracted 78 physical movie features. Secondly, we constructed a 2-D psychological space, called an emotional space, consisting of(tension-relax)axis and(refreshing-gloomy)axis, and narrowed 30 from 78 possible movie features not using a physiological experiment but a psychological one.In the second step, “extracting relationship between movie features and physiological responses, “we firstly made abstract experimental movie scenes with 20 different variables of one feature that shown the highest correlation among 30 features. Since movie context, i.e. story, deeply influences to human emotion, we made the abstract movie scenes to avoid its effect. Secondly, we measured physiological data by displaying the abstract movies. Measured data are EEG at two side points and two back side, ECG, sweating rate, blood pressure level, and finger pulse volume. However, the difference of measured data among subjects was bigger than the difference of values of physical movie features, we have not found out the significant relationship between the movie features and physiological responses yet.In the third step," establishing driving emotion using extended interactive evolutionary computation(IEC),"we aimed to establish a technique to optimize movie features to drive a movie viewer's physiological condition to a given target condition. Since we have not found out the movie features that surely drive human physiology in the second step, we focused on improving IEC technique. What we did was combining IEC with evolutionary multi-objective optimization, introducing Particle Swarm Optimization instead of evolutionary computation, introducing IEC user's evaluation model, and others.