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.

Members
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Research themes

of Cape (2023―)

A production support system for wind-deformed animation of cape


Visual analysis of leading lines based on differential topology
Suspended themes

Portraits (2023―2024)

Generation of complementary background images for portrait illustrations using interactive genetic algorithm

(2022―2023)

A house dance design system
based on constructive choreographic process

Retouching (2021―2022)

Photo retouching for mixed painting material style in digital illustrations

(2020―2021)

Gernerating naturally animated crowd scenes with non-player characters based on arousal-valence model

(2019―2021)

Automatic generation of 3D natural Anime-like non-player characters with machine learning