用眼动追踪和智能生成,让设计效率提升4倍以上。
Attention is also needed for form design
- 通过虚拟现实眼动捕捉设计师的潜意识偏好,结合智能代理生成设计。
- 自动化流程比传统方法快4倍以上,且设计质量在8项指标上均更优。
- 适合想提升设计效率与创意质量的工业设计师或AI应用研究者。
传统产品设计过程耗时、依赖主观经验,且灵感到概念的转化不透明。本文提出一种注意力感知框架,融合两个协同系统:EUPHORIA(基于眼动追踪的沉浸式虚拟现实环境,隐式捕捉审美偏好)与RETINA(智能代理流程,将偏好转化为具体设计输出)。两阶段研究验证了注意力与显性偏好、情绪之间的关联。四名设计师在四种工作流下完成挑战性设计任务,集成的EUPHORIA-RETINA流程比传统方法快4倍以上。50位设计专家评估16个最终渲染图,全自动系统生成的设计在8个维度(新颖性、视觉吸引力、情感共鸣等)上得分最高,其价值度(基于逆Plackett-Luce模型与梯度下降优化计算)显著领先。该研究推动从传统计算机辅助设计(CAD)向人机协同设计(DAC)范式转变,将设计师角色升级为创意总监,实现人类直觉与生成式AI的高效协同。
原文摘要 · Abstract (English)
Conventional product design is a cognitively demanding process, limited by its time-consuming nature, reliance on subjective expertise, and the opaque translation of inspiration into tangible concepts. This research introduces a novel, attention-aware framework that integrates two synergistic systems: EUPHORIA, an immersive Virtual Reality environment using eye-tracking to implicitly capture a designer's aesthetic preferences, and RETINA, an agentic AI pipeline that translates these implicit preferences into concrete design outputs. The foundational principles were validated in a two-part study. An initial study correlated user's implicit attention with explicit preference and the next one correlated mood to attention. A comparative study where 4 designers solved challenging design problems using 4 distinct workflows, from a manual process to an end-to-end automated pipeline, showed the integrated EUPHORIA-RETINA workflow was over 4 times more time-efficient than the conventional method. A panel of 50 design experts evaluated the 16 final renderings. Designs generated by the fully automated system consistently received the highest Worthiness (calculated by an inverse Plackett-Luce model based on gradient descent optimization) and Design Effectiveness scores, indicating superior quality across 8 criteria: novelty, visual appeal, emotional resonance, clarity of purpose, distinctiveness of silhouette, implied materiality, proportional balance, & adherence to the brief. This research presents a validated paradigm shift from traditional Computer-Assisted Design (CAD) to a collaborative model of Designer-Assisting Computers (DAC). By automating logistical and skill-dependent generative tasks, the proposed framework elevates the designer's role to that of a creative director, synergizing human intuition with the generative power of agentic AI to produce higher-quality designs more efficiently.
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