Pic2PolyArt: Transforming a photograph into polygon-based geometric art

Pau Ek Low, Lai Kuan Wong*, John See, Ruisheng Ng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Geometric art, an artwork that is structured by geometric shapes, was first made popular by the introduction of Cubism paintings by Pablo Picasso and Georges Braque in the early-20th-century. With the recent advancement in digital imaging technology coupled with the rising popularity of social media such as Instagram, automatic geometric abstraction that can automatically transform a photograph into a piece of geometric art starts to gain research attention. Several state-of-the-art works have been proposed. Notably, despite the fact that Cubism artworks by renown artists illustrate the importance of the main subject in a painting to be recognizable and should be given more detailed representation, most of the state-of-the-art abstraction algorithms are not subject-focused. In this paper, we present Pic2PolyArt, a unified subject-focused geometric abstraction framework that can support both triangle-based and polygon-based abstraction. Given an input photograph, our proposed algorithm first identifies the main subject and important features of an image with a combination of saliency, edge, and face detection techniques. It then generates a set of seed points that are used by Delaunay Triangulation and Voronoi Tessellation to generate triangle-based and polygon-based geometric abstraction respectively. Results from qualitative evaluation on benchmark dataset and empirical user studies demonstrate the effectiveness of our proposed abstraction framework in generating pleasant geometric abstraction from photographs and provide insightful knowledge on users preference with regards to the type of polygons and the level of abstraction used to represent the resulting geometric art.

Original languageEnglish
Article number116090
JournalSignal Processing: Image Communication
Early online date1 Dec 2020
Publication statusPublished - Feb 2021


  • Computational art
  • Geometric art
  • Low poly rendering
  • Non-photorealistic rendering
  • Style transfer

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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