首页> 外文会议>Computer vision and image analysis of art II >Improved curvature-based inpainting applied to fine art: Recovering van Gogh's partially hidden brush strokes
【24h】

Improved curvature-based inpainting applied to fine art: Recovering van Gogh's partially hidden brush strokes

机译:改进的基于曲率的喷漆应用于美术:恢复梵高部分隐藏的笔触

获取原文
获取原文并翻译 | 示例

摘要

Underdrawings and pentimenti-typically revealed through x-ray imaging and infrared reflectography-comprise important evidence about the intermediate states of an artwork and thus the working methods of its creator.* To this end, Shahram, Stork and Donoho introduced the De-pi ct algorithm, which recovers layers of brush strokes in paintings with open brush work where several layers are partially visible, such as in van Gogh's Self portrait with a grey felt hat.2 While that preliminary work served as a proof of concept that computer image analytic methods could recover some occluded brush strokes, the work needed further refinement before it could be a tool for art scholars. Our current work makes several steps to improve that algorithm. Specifically, we refine the inpainting step through the inclusion of curvature-based constraints, in which a mathematical curvature penalty biases the reconstruction toward matching the artist's smooth hand motion. We refine and test our methods using "ground truth" image data: passages of four layers of brush strokes in which the intermediate layers were recorded photographically. At each successive top layer (currently identified by the user), we used k-means clustering combined with graph cuts to obtain chromatically and spatially coherent segmentation of brush strokes. We then reconstructed strokes at the deeper layer with our new curvature-based inpainting algorithm based on chromatic level lines. Our methods are clearly superior to previous versions of the De-pict algorithm on van Gogh's works giving smoother, natural strokes that more closely match the shapes of unoccluded strokes. Our improved method might be applied to the classic drip paintings of Jackson Pollock, where the drip work is more open and the physics of splashing paint ensures that the curvature more uniform than in the brush strokes of van Gogh.
机译:通过X射线成像和红外反射照相术得出的未完成部分和露点图通常包含有关艺术品的中间状态以及其创作者的工作方法的重要证据。*为此,Shahram,Stork和Donoho引入了De-pict该算法可在部分可见的几层开放式笔刷作品中恢复绘画笔触的图层,例如在梵高的“戴灰色毡帽的自画像”中。2虽然该初步作品是计算机图像分析方法的概念证明可以恢复一些被遮挡的笔触,这项工作需要进一步完善才能成为艺术学者的工具。我们当前的工作分几步来改进该算法。具体来说,我们通过包含基于曲率的约束条件来优化修复步骤,其中数学曲率罚分使重建偏向于与艺术家的平滑手部运动相匹配。我们使用“地面真相”图像数据完善和测试我们的方法:四层画笔描边的段落,中间层通过照相方式记录。在每个连续的顶层(当前由用户标识),我们使用k-均值聚类和图割相结合以获得笔触的色度和空间相干分割。然后,我们使用新的基于色度水平线的基于曲率的修复算法在更深的层重建笔触。我们的方法明显优于Van Gogh作品中的De-pict算法的先前版本,它提供了更平滑自然的笔触,与未遮挡的笔触形状更加匹配。我们改进的方法可能会应用于杰克逊·波洛克(Jackson Pollock)的经典滴油画中,在滴油工作中,滴油工作更加开放,并且泼墨的物理特性可确保曲率比梵高的画笔笔触更为均匀。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号