Normal manipulation for bas-relief modeling

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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  • Zhongping Ji
  • Xianfang Sun
  • Yu-Wei Zhang
  • Weiyin Ma
  • Mingqiang Wei

Related Research Unit(s)


Original languageEnglish
Article number101099
Journal / PublicationGraphical Models
Online published17 Feb 2021
Publication statusPublished - Mar 2021


We introduce a normal-based modeling framework for bas-relief generation and stylization which is motivated by the recent advancement in this topic. Creating bas-relief from normal images has successfully facilitated bas-relief modeling in image space. However, the use of normal images in previous work is restricted to the cut-and-paste or blending operations of layers. These operations simply treat a normal vector as a pixel of a general color image. This paper is intended to extend normal-based methods by processing the normal image from a geometric perspective. Our method can not only generate a new normal image by combining various frequencies of existing normal images and details transferring, but also build bas-reliefs from a single RGB image and its edge-based sketch lines. In addition, we introduce an auxiliary function to represent a smooth base surface or generate a layered global shape. To integrate above considerations into our framework, we formulate the bas-relief generation as a variational problem which can be solved by a screened Poisson equation. One important advantage of our method is that it can generate more styles than previous methods and thus it expands the bas-relief shape space. We experimented our method on a range of normal images and it compares favorably to other popular classic and state-of-the-art methods.

Research Area(s)

  • Bas-relief, Detail transfer, Height field, Normal image, Screened Poisson equation, Variational optimization

Citation Format(s)

Normal manipulation for bas-relief modeling. / Ji, Zhongping; Sun, Xianfang; Zhang, Yu-Wei; Ma, Weiyin; Wei, Mingqiang.

In: Graphical Models, Vol. 114, 101099, 03.2021.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review