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Using attentional highlighting to train visual expertise.

机译:使用注意力突出显示来训练视觉技能。

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摘要

Our goal is to develop a paradigm to train novices on complex visual tasks more efficiently. We explore the value of attentional highlighting---which involves making saliency modulations to guide novices---by studying the domain of fingerprint matching. Using data collected by Busey et al. (in press) we construct probabilistic models to predict fixation sequences of novices and experts. We then conduct experiments with novices and record eye gaze as they examine prints for similarities and differences. During a training phase, attentional highlighting cues subjects along an expert fixation path. We evaluate the effect of training by comparing pre- and post-training performance on a set of images including training and transfer images. Using our models, we compute a log odds score that reflects the degree of expertise exhibited by a subject's fixation sequences. Our results show that the gaze behavior of subjects becomes more expert-like on trained and untrained images.
机译:我们的目标是开发一种范例,以更有效地培训新手进行复杂的视觉任务。我们通过研究指纹匹配的领域来探索注意力突出显示的价值-涉及进行显着性调制以指导新手-。使用由Busey等收集的数据。 (印刷中)我们构建概率模型来预测新手和专家的固定顺序。然后,我们与新手进行实验,并在他们检查印刷品的异同时记录视线。在训练阶段,注意力突出显示提示沿专家注视路径的主题。我们通过比较训练前和训练后对一组图像(包括训练图像和传递图像)的表现来评估训练的效果。使用我们的模型,我们计算出对数赔率得分,该得分反映了受试者注视序列所展现出的专业水平。我们的结果表明,在经过训练和未经训练的图像上,对象的凝视行为变得更像专家。

著录项

  • 作者

    Roads, Brett David.;

  • 作者单位

    University of Colorado at Boulder.;

  • 授予单位 University of Colorado at Boulder.;
  • 学科 Computer Science.;Psychology Cognitive.
  • 学位 M.S.
  • 年度 2013
  • 页码 55 p.
  • 总页数 55
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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