Cheng Shenghe
College of Art, Nanjing University, Nanjing, China.
Front Psychol. 2021 Aug 19;12:730066. doi: 10.3389/fpsyg.2021.730066. eCollection 2021.
Emotion is a unique ability possessed by human beings as advanced creatures. Emotions give people a unique physical and mental experience. Assigning emotions to computer systems is one of the latest topics in artificial intelligence research. The purpose is to allow machines to achieve natural coordination between humans and computers. This article focuses on the visual expression of emotion in the dynamic three-dimensional painting system, creating an intelligent painting system and realizing a good user experience. In this paper, the discrete method is used to qualitatively analyze emotions, and the continuous method is used to quantify basic emotions, and emotional modeling and emotional quantitative analysis are proposed to realize quantitative analysis of emotions. Combining these two methods, a comprehensive method is proposed, which uses a continuous method to quantify the basic emotions of each discrete dimension, and finally superimposes them into a comprehensive emotional synthesis model. Emotion modeling is the basis of emotion visualization. Borrowing the relationship between emotion synthesis model and visual emotion elements, this article puts forward the concept of qualitative and quantitative visual emotion elements, and expounds that the multidimensional superposition of visual emotion elements makes dynamic three-dimensional painting system emotions. The experimental results in this article show that the emotional visualization scheme of 100 samples is tested by quantitative statistical methods to demonstrate its effectiveness. Starting from 5 points of concern, the emotion visualization method discussed in this article can indeed convey or suggest a certain positive emotion (the average value of experience, transitivity, and infectiousness > 2.5, and the variance is close to 0), but we also found this recognition at the same time The degree is not high enough, and individual differences are large (mean value < 2.5, variance close to 1). This can indicate that different subjects have different feelings and evaluations of this emotional visualization. As long as the difference is within a reasonable range, this emotional visualization also has practical value, and has the ability to convey or suggest emotions.
情感是人类作为高级生物所拥有的独特能力。情感给予人们独特的身心体验。将情感赋予计算机系统是人工智能研究的最新课题之一。目的是让机器实现人与计算机之间的自然协调。本文聚焦于动态三维绘画系统中情感的视觉表达，创建智能绘画系统并实现良好的用户体验。本文采用离散方法对情感进行定性分析，采用连续方法对基本情感进行量化，并提出情感建模和情感定量分析以实现情感的定量分析。结合这两种方法，提出一种综合方法，即使用连续方法对每个离散维度的基本情感进行量化，最后将它们叠加到一个综合情感合成模型中。情感建模是情感可视化的基础。借鉴情感合成模型与视觉情感元素之间的关系，本文提出定性和定量视觉情感元素的概念，并阐述视觉情感元素的多维叠加构成了动态三维绘画系统的情感。本文的实验结果表明，通过定量统计方法对100个样本的情感可视化方案进行测试，以证明其有效性。从5个关注点出发，本文所讨论的情感可视化方法确实能够传达或暗示某种积极情感（体验、传递性和感染力的平均值>2.5，且方差接近0），但同时我们也发现这种识别程度不够高，个体差异较大（平均值<2.5，方差接近1）。这表明不同的受试者对这种情感可视化有不同的感受和评价。只要差异在合理范围内，这种情感可视化也具有实用价值，并且具有传达或暗示情感的能力。
