Computational aesthetics analyzes various expressions arising in art and music works from an aesthetic perspective, and strives to utilize them for the purpose of re-synthesis. Evaluation of such diverse expressions, including exaggeration and omission, is not unified; it does change depending on the intention of the creator and the taste of a person who appreciates the work. This team pursues computational approaches to identification of aesthetic elements.
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Members
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Research themes
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of Cape (2023―)
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A production support system for wind-deformed animation of cape
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Visual analysis of leading lines based on differential topology
Suspended themes
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Portraits (2023―2024)
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Generation of complementary background images for portrait illustrations using interactive genetic algorithm
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(2022―2023)
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A house dance design system
based on constructive choreographic process
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Retouching (2021―2022)
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Photo retouching for mixed painting material style in digital illustrations
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(2020―2021)
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Gernerating naturally animated crowd scenes with non-player characters based on arousal-valence model
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(2019―2021)
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Automatic generation of 3D natural Anime-like non-player characters with machine learning