Multidimensional Visualization to Support Analysis of Image Collections

Abstract

Multidimensional visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces a methodology and a software tool called PEx-Image - Projection Explorer for Image for analysis and exploration of image collections employing visualizations. The visual mappings proposed here are similarity-based multidimensional projections and point placements, which layout the data on a plane for visual exploration. The proposed approach supports various image analysis tasks such as feature selection and classification, improving data exploration capabilities. We also illustrate how it can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.