Scale-aware Black-and-White Abstraction of 3D Shapes

You-En Lin, Yongliang Yang, Hung-Kuo Chu

Research output: Contribution to journalArticlepeer-review

5 Citations (SciVal)
314 Downloads (Pure)

Abstract

Flat design is a modern style of graphics design that minimizes the number of design attributes required to convey 3D shapes. This approach suits design contexts requiring simplicity and efficiency, such as mobile computing devices. This 'less-is-more' design inspiration has posed significant challenges in practice since it selects from a restricted range of design elements (e.g., color and resolution) to represent complex shapes. In this work, we investigate a means of computationally generating a specialized 2D flat representation - image formed by black-and-white patches - from 3D shapes.We present a novel framework that automatically abstracts 3D man-made shapes into 2D binary images at multiple scales. Based on a set of identified design principles related to the inference of geometry and structure, our framework jointly analyzes the input 3D shape and its counterpart 2D representation, followed by executing a carefully devised layout optimization algorithm. The robustness and effectiveness of our method are demonstrated by testing it on a wide variety of man-made shapes and comparing the results with baseline methods via a pilot user study. We further present two practical applications that are likely to benefit from our work.

Original languageEnglish
Article number117
Pages (from-to)1-11
Number of pages11
JournalACM Transactions on Graphics
Volume37
Issue number4
Early online date31 Jul 2018
DOIs
Publication statusPublished - 31 Aug 2018

Keywords

  • Black-and-white image
  • Joint 2D/3D analysis
  • Layout optimization
  • Scale-aware abstraction

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

Fingerprint

Dive into the research topics of 'Scale-aware Black-and-White Abstraction of 3D Shapes'. Together they form a unique fingerprint.

Cite this