Fast content-aware resizing of multi-layer information visualization via adaptive triangulation

Chenhui Li, George Baciu, Yunzhe Wang, Xiujun Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Visual graphics and image-based content have become the pervasive modes of interaction with the digital information flow. With the immense proliferation of display systems and devices, visual content representation has become increasingly challenging. Classical static image resizing algorithms are not directly suitable for the current dynamic information visualization of streaming data flows and processes because most of the visual content often consists of superimposed, multi-layered, multi-scale structure. In this paper, we propose a new adaptive method for content-aware resizing of visual information flow. Scaling is performed by deforming a hierarchical triangle mesh that matches the visual saliency map (VSM) of the streaming data. The VSM is generated automatically based on a series of predefined rules operating on a triangular mesh representation of visual features. We present a linear energy function to minimize distortions of the triangular deformations to perceptually preserve informative content. Through multiple experiments on real datasets, we show that the method has both high performance as well as high robustness in the presence of large differences in the visual aspect ratios between target displays.

Original languageEnglish
Pages (from-to)61-73
Number of pages13
JournalJournal of Visual Languages and Computing
Volume45
DOIs
Publication statusPublished - 1 Apr 2018

Keywords

  • Content-aware resizing
  • Context preserving
  • Focus+context
  • Information visualization
  • Saliency map
  • Triangulation

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Computer Science Applications

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