Hybrid image/model-based gaze-contingent rendering

  • Authors:
  • Hunter A. Murphy;Andrew T. Duchowski;Richard A. Tyrrell

  • Affiliations:
  • Clemson University, Clemson, USA;Clemson University, Clemson, USA;Clemson University, Clemson, USA

  • Venue:
  • ACM Transactions on Applied Perception (TAP)
  • Year:
  • 2009

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Abstract

A nonisotropic hybrid image/model-based gaze-contingent rendering technique utilizing ray casting on a GPU is discussed. Empirical evidence derived from human subject experiments indicates an inverse relationship between a peripherally degraded scene's high-resolution inset size and mean search time, a trend consistent with existing image-based and model-based techniques. In addition, the data suggest that maintaining a target's silhouette edges decreases search times when compared to targets with degraded edges. However, analysis suggests a point of diminishing returns with an inset larger than 15° when target discrimination is a component of visual search. Benefits of the hybrid technique include simplicity of design and parallelizability, both conducive to GPU implementation.