情感驱动的智能艺术研究综述

Review of Emotion-driven Artificial Intelligent Art Research

中文关键词: 人工智能艺术  情感计算  情感艺术数据库  情感驱动的艺术生成

英文关键词: artificial intelligence art  affective computing  affective art database  emotion-driven art generation

中文摘要:

      目的 从数据、方法，以及应用三方面梳理情感化智能艺术的研究现状，并总结该领域的发展历程、局限性及未来研究趋势。方法 基于当前的文献、研究成果与应用产品，回顾了情感标注方式的变化及其对情感艺术数据库的影响。解释了情感识别、可控生成、跨媒体等智能技术的实现原理，以及多种情感驱动的智能艺术方法。总结了三种情感与智能艺术的交互机制，以及代表性产品对医疗健康、文化教育、商业营销等领域的影响。结论 情感化方法提升了智能作品的感染力，支持了艺术创作中的人机协同。随着艺术与技术的进一步融合，艺术领域将迎来新的生产、体验与消费模式。

英文摘要:

      The work aims to sort out the current research status of emotion-driven AI art from three aspects: data, methods, and applications, and summarize the development history, limitations, and future research trends in this field. First, based on the literature, research results, and application products, the changes in emotion annotation methods and their impacts on affective art databases were reviewed. Then, the implementation principles of technologies such as emotion recognition, controllable generation, and cross-media search were explained, and a variety of emotion-driven AI artistic methods were discussed. Finally, three interaction mechanisms between emotion and AI art were summarized, and the impact of related products on creativity, healthcare, education, and business marketing was analyzed. Affective computing methods enhance the infectiousness of AI artworks and support human-AI co-creation. With the further integration of art and technology, the art field will usher in new modes of production, experience, and consumption.