Paper Info
Title
Fast content-aware resizing of multi-layer information visualization via adaptive triangulation.
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.
Year
DOI
Venue
2018
10.1016/j.jvlc.2017.03.004
Journal of Visual Languages & Computing
Keywords
Field
DocType
Content-aware resizing,Information visualization,Triangulation,Saliency map,Context preserving,Focus+context
Graphics,Computer vision,Aspect ratio (image),Information flow (information theory),Information visualization,Computer science,Robustness (computer science),Triangulation (social science),Artificial intelligence,Scaling,Triangle mesh
Journal
Volume
ISSN
Citations 
45
1045-926X
0
PageRank 
References 
Authors
0.34
23
4
Name
Order
Citations
PageRank
Chenhui Li12711.16
George Baciu240956.17
Yunzhe Wang353.80
Xiujun Zhang4212.39