Visual Perception and Mixed-Initiative Interaction for Assisted Visualization Design

This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search strategy. The result is a visualization assistant called ViA, a system that collaborates with its users to identify perceptually salient visualizations for large, multidimensional datasets. ViA applies knowledge of low-level human vision to: (1) evaluate the effectiveness of a particular visualization for a given dataset and analysis tasks; and (2) rapidly direct its search towards new visualizations that are most likely to offer improvements over those seen to date. Context, domain expertise, and a high-level understanding of a dataset are critical to identifying effective visualizations. We apply a mixed-initiative strategy that allows ViA and its users to share their different strengths and continually improve ViA's understanding of a user's preferences. We visualize historical weather conditions to compare ViA's search strategy to exhaustive analys...

• Type: Journal
• Year: 2008
• Where: TVCG
• Authors: Christopher G. Healey, Sarat Kocherlakota, Vivek Rao, Reshma Mehta, Robert St. Amant
• Keywords: Human Vision, Perceptual Guidelines, Search Strategy, TVCG 2008