Eye-tracking Investigation During Visual Analysis of Projected Multidimensional Data with 2D Scatterplots

• DOI: 10.5220/0004675802330246
• Publication Date: 2014-01-21T10:45:56Z
• Authors: Ronak Etemadpour; Bettina Olk; Lars Linsen
• Keywords: Visual Search

A common strategy for visual encoding of multidimensional data analyses is to use dimensionality reduction. Each point projected a 2D using certain the layout. Many layout strategies have been proposed addressing different objectives and targeted at distinct domains applications. The resulting information typically displayed in form scatterplots. user's perspective such as role attention guidance respective task has not addressed much. It goal this work investigate, how characteristics affect cognitive process during completion. Eye trackers are an effective means capture over time. We eye tracking user study, where we ask users perform typical analysis tasks relation seeking, behavior comparison, pattern identification. Those often involve detecting correlating clusters. To understand density within clusters, cluster sizes, shapes, first conducted study with synthetic scatterplots, can set properties manually. evaluate changing various parameters correlate it correctness answer. In second step, were asked complete on real-world (image collection document collection) that visualized selection reduction algorithms. transfer insight obtained from investigate decision making data. Gestalt laws be applied structure. examine techniques produce change pattern. draw some conclusions projection methods support or hinder leading guidelines.