Exploring new qualitative methods to support a quantitative analysis of glance behavior

Mauricio Muñoz, B. Reimer, Bruce Mehler
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引用次数: 8

Abstract

The work proposes conceptual ways of considering drivers' visual behavior over time as a flow of attention across space. These efforts extend upon previous works (research and regulatory) that focus in greater detail on quantifying attention independent of time. The primary contribution of this work lies in the presented methodology for analysis of glance allocation features. An application of this method is explored as an illustration of its analytic potential. Driver glance allocation data were drawn from a heterogeneous set of drivers. Double coded and mediated glance allocations were used to detail differences between drivers' visual behavior across 3 different task types (baseline driving, visual-manual interaction, auditory-vocal interaction). Glance transition counts were used to estimate glance transition probabilities and significance values. Glance duration features were explored in parallel and used to visualize temporal allocation distribution and significance. Results show that visualization techniques based on these features are well suited for qualitative analysis of visual attention.
探索新的定性方法来支持一瞥行为的定量分析
这项工作提出了概念性的方法,将驾驶员的视觉行为随着时间的推移视为注意力在空间中的流动。这些努力扩展了之前的工作(研究和监管),这些工作更详细地关注于量化与时间无关的注意力。这项工作的主要贡献在于提出了分析目光分配特征的方法。探讨了该方法的应用,以说明其分析潜力。司机目光分配数据是从一组异构的司机中提取的。采用双编码和介导的眼神分配方法,详细分析了3种不同任务类型(基线驾驶、视觉-手动交互、听觉-声音交互)中驾驶员视觉行为的差异。使用目光转移计数来估计目光转移概率和显著性值。同时探索了浏览持续时间特征,并将其用于可视化时间分配分布和意义。结果表明,基于这些特征的可视化技术非常适合于视觉注意的定性分析。
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