Scattering Points in Parallel Coordinates

  • Authors:

  • Xiaoru Yuan;Peihong Guo;He Xiao;Hong Zhou;Huamin Qu

  • Affiliations:

  • Key Laboratory of Machine Perception & Peking University;Key Laboratory of Machine Perception & Peking University;Key Laboratory of Machine Perception & Peking University;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology

  • Venue:
  • IEEE Transactions on Visualization and Computer Graphics
  • Year:
  • 2009

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Abstract

In this paper, we present a novel parallel coordinates design integrated with points (Scattering Points in Parallel Coordinates, SPPC), by taking advantage of both parallel coordinates and scatterplots. Different from most multiple views visualization frameworks involving parallel coordinates where each visualization type occupies an individual window, we convert two selected neighboring coordinate axes into a scatterplot directly. Multidimensional scaling is adopted to allow converting multiple axes into a single subplot. The transition between two visual types is designed in a seamless way. In our work, a series of interaction tools has been developed. Uniform brushing functionality is implemented to allow the user to perform data selection on both points and parallel coordinate polylines without explicitly switching tools. A GPU accelerated Dimensional Incremental Multidimensional Scaling (DIMDS) has been developed to significantly improve the system performance. Our case study shows that our scheme is more efficient than traditional multi-view methods in performing visual analysis tasks.