Automatic transfer of musical mood into virtual environments

Sangyoon Han, Amit Bhardwaj, Seungmoon Choi
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Abstract

This paper presents a method that automatically transforms a virtual environment (VE) according to the mood of input music. We use machine learning to extract a mood from the music. We then select images exhibiting the mood and transfer their styles to the textures of objects in the VE photorealistically or artistically. Our user study results indicate that our method is effective in transferring valence-related aspects, but not arousal-related ones. Our method can still provide novel experiences in virtual reality and speed up the production of VEs by automating its procedure.
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自动将音乐情绪转移到虚拟环境中
本文提出了一种根据输入音乐的情绪自动转换虚拟环境的方法。我们用机器学习从音乐中提取情绪。然后,我们选择表现情绪的图像,并将其风格转移到VE中逼真或艺术的物体纹理上。我们的用户研究结果表明,我们的方法在转移与价相关的方面是有效的,而不是与唤醒相关的方面。该方法可以为虚拟现实提供新颖的体验,并通过自动化过程加快虚拟现实的生产速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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