材料指纹:通过心理物理分析和神经网络预测人类对物质外观的感知
Jiri Filip1, Filip Dechterenko2, Filipp Schmidt3
1Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic.
Royal Society open science
|November 17, 2025
概括
研究人员开发了一个"视觉指纹"来预测人类如何从图像中感知材料. 这种方法只使用两个图像准确预测外观和相似性,简化了数字材料的表示.
科学领域:
- 计算机视觉 计算机视觉
- 人与计算机的交互
- 材料科学 材料科学 材料科学
背景情况:
- 数字材料的表现对于VR,设计和质量控制至关重要.
- 从图像中预测人类对材料的感知是复杂的,因为视觉的复杂性.
- 现有的方法很难将图像数据与人类可以理解的物质属性联系起来.
研究的目的:
- 引入"视觉指纹",用于感知物质表示.
- 将基于图像的测量与直观,人类可以理解的属性联系起来.
- 从视觉数据开发材料感知的预测框架.
主要方法:
- 通过347种不同的现实世界材料进行了心理物理研究.
- 收集了超过11万人的评分在16个关键的外观属性.
- 集成的CLIP衍生图像功能与多层感知子模型.
主要成果:
- 开发了一个物质感知的预测框架.
- 准确地预测了人类对物质外观和相似性的判断.
- 通过每种材料只使用两张图像,证明了准确的预测.
结论:
- "视觉指纹"为物质表示提供了一种实用,可解释的方法.
- 能够在数字应用中进行直观的比较和检索.
- 在数字环境中提升对材料性能的理解和互操作性.
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