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Cognitive theme preserving color transfer for fabric design

机译:保留色彩设计的认知主题,用于织物设计

摘要

The authors present a fully automatic method of color theme extraction and transfer for fabric color design. For real-life fabrics, such extraction and transfer is performed through a highly time consuming and knowledge intensive process, known as color theme design. Specifically color and tone style adjustments are part of a generic process of cognition involved in the creation of new fabric designs. The authors explicitly formalize the process of color theme extraction from a set of images as a process of color mood based hierarchical data clustering and optimization. They begin with image sorting within a cognitive theme and color compatibility learning from large datasets. They then propose fully automatic color-texture association and color transfer algorithms which satisfy the criteria used in professional fabric pattern design while ensuring the plausibility of the cognitive theme preserved color transfer from the images to fabric patterns. Lastly, the color transfer process is formulated as a constrained optimization problem that is solved efficiently by total variation minimization. The use of color theme associations can automatically generate new fabric designs that rival complex commercial designs that are otherwise difficult to generate even by experienced designers. The authors’ fully automatic color theme preserving transfer method leads to a new approach to fabric design that significantly save time and cost for both fashion designers and computer artists.
机译:作者提出了一种用于织物颜色设计的自动提取和转移颜色主题的方法。对于现实生活中的织物,此类提取和转移是通过高度耗时且知识密集的过程(称为色彩主题设计)执行的。具体来说,颜色和色调样式的调整是创建新织物设计所涉及的一般认知过程的一部分。作者明确将一组图像中的颜色主题提取过程正式化为基于颜色心情的分层数据聚类和优化过程。他们从认知主题内的图像排序和从大型数据集中学习颜色兼容性开始。然后,他们提出了全自动的颜色纹理关联和颜色转移算法,这些算法可以满足专业织物图案设计中使用的标准,同时确保保留从图像到织物图案的颜色转移的认知主题的合理性。最后,将颜色转移过程公式化为约束优化问题,可以通过使总变化最小化有效地解决该问题。使用颜色主题关联可以自动生成新的面料设计,该面料设计可以与复杂的商业设计相媲美,否则即使是经验丰富的设计师也很难生成。作者的全自动色彩主题保存转移方法导致了一种新的面料设计方法,为服装设计师和计算机艺术家节省了时间和成本。

著录项

  • 作者

    Zheng D; Baciu G; Han Y; Hu J;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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