Exploring Interactive Color Palettes for Abstraction-Driven Exploratory Image Colorization

要旨

Color design is essential in areas such as product, graphic, and fashion design. However, current tools like Photoshop, with their concrete-driven color manipulation approach, often stumble during early ideation, favoring polished end results over initial exploration. We introduced Mondrian as a test-bed for abstraction-driven approach using interactive color palettes for image colorization. Through a formative study with six design experts, we selected three design options for visual abstractions in color design and developed Mondrian where humans work with abstractions and AI manages the concrete aspects. We carried out a user study to understand the benefits and challenges of each abstraction format and compare the Mondrian with Photoshop. A survey involving 100 participants further examined the influence of each abstraction format on color composition perceptions. Findings suggest that interactive visual abstractions encourage a non-linear exploration workflow and an open mindset during ideation, thus providing better creative affordance.

著者
Xinyu Shi
University of Waterloo, Waterloo, Ontario, Canada
Mingyu Liu
University of Waterloo, Waterloo, Ontario, Canada
Ziqi Zhou
University of Waterloo, Waterloo, Ontario, Canada
Ali Neshati
Ontario Tech University, Oshawa, Ontario, Canada
Ryan Rossi
Adobe Research, San Jose, California, United States
Jian Zhao
University of Waterloo, Waterloo, Ontario, Canada
論文URL

https://doi.org/10.1145/3613904.3642223

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Colors

313B
5 件の発表
2024-05-15 01:00:00
2024-05-15 02:20:00