Object displays for identifying multidimensional outliers within a crowded visual periphery

  • Authors:
  • Mikko Berg;Ilpo Kojo;Jari Laarni

  • Affiliations:
  • Helsinki School of Economics (HSE), Center for Knowledge and Innovation Research, P.O. Box 1210, 00101 Helsinki, Finland and Aalto University, Department of Media Technology, P.O. Box 5400, 02015 ...;Helsinki School of Economics (HSE), Center for Knowledge and Innovation Research, P.O. Box 1210, 00101 Helsinki, Finland;VTT Technical Research Centre of Finland (VTT), P.O. Box 1000, 02044 VTT Espoo, Finland

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2010

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Abstract

This article discusses the human ability to detect, locate, or identify objects and their features using peripheral vision. The potential of peripheral vision is underused with user interfaces probably due to the limits of visual acuity. Peripheral preview can guide focused attention to informative locations, if the visual objects are large enough and otherwise within the limits of discrimination. Our experiments focused on the task of identifying an outlier and implicated another limiting factor, crowding, for integration of object features. The target object and the corresponding data dimension were located from an object display representation used for integrating multidimensional data. We measured performance on a peripheral vision task in terms of reaction times and eye movements. Subjects identified the target item from 480 alternatives within 100ms. Therefore, the identification process would not slow down the natural gaze sequence and focused attention during monitoring and data mining tasks.