The increasing interest in the effects of emotion on cognitive, social, and neural processes creates a constant need for efficient and reliable techniques for emotion elicitation. Emotions are important in many areas, especially in advertising design and video production. The impact of emotions on the audience plays an important role. This paper analyzes the physical elements in a two-dimensional emotion map by extracting the physical elements of a video (color, light intensity, sound, etc.). We used k-nearest neighbors (K-NN), support vector machine (SVM), and multilayer perceptron (MLP) classifiers in the machine learning method to accurately predict the four dimensions that express emotions, as well as summarize the relationship between the two-dimensional emotion space and physical elements when designing and producing video.

中文翻译：

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根据视频的物理元素识别情绪。

人们对情感对认知，社交和神经过程的影响的兴趣日益浓厚，这导致人们不断需要有效，可靠的情感诱发技术。情绪在许多领域都很重要，尤其是在广告设计和视频制作中。情绪对听众的影响起着重要作用。本文通过提取视频的物理元素（颜色，光强度，声音等）来分析二维情感图中的物理元素。我们在机器学习方法中使用了k最近邻（K-NN），支持向量机（SVM）和多层感知器（MLP）分类器来准确预测表达情感的四个维度，并总结两者之间的关系设计和制作视频时的三维情感空间和物理元素。