探索用于抽象驱动的探索式图像着色的交互式调色板
Exploring Interactive Color Palettes for Abstraction-Driven Exploratory Image Colorization
AI总结：
本文提出 Mondrian 试验平台，以交互式调色板支持抽象驱动的图像着色，并通过专家研究、用户比较和百人调查验证其对早期创意探索的促进作用。
摘要：
色彩设计在产品、平面和时装设计等领域至关重要。然而，当前诸如 Photoshop 之类的工具采用具体驱动的色彩操控方式，往往在早期构思阶段受挫，更偏向精致的最终结果而非初始探索。我们推出了 Mondrian，作为使用交互式调色板进行图像着色的抽象驱动方法的试验平台。通过对六位设计专家开展的一项形成性研究，我们为色彩设计中的视觉抽象选择了三种设计方案，并开发了 Mondrian：在该系统中，人类处理抽象内容，而 AI 管理具体方面。我们开展了一项用户研究，以理解每种抽象形式的优势与挑战，并将 Mondrian 与 Photoshop 进行比较。一项涉及100名参与者的调查进一步考察了每种抽象形式对色彩构成感知的影响。研究结果表明，交互式视觉抽象鼓励非线性探索工作流以及构思过程中的开放心态，从而提供更好的创造可供性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
