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Modeling peripheral visual acuity enables discovery of gaze strategies at multiple time scales during natural scene search

机译:对外围视敏度进行建模可以在自然场景搜索期间在多个时间尺度上发现注视策略

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摘要

Like humans, monkeys make saccades nearly three times a second. To understand the factors guiding this frequent decision, computational models of vision attempt to predict fixation locations using bottom-up visual features and top-down goals. How do the relative influences of these factors evolve over multiple time scales? Here we analyzed visual features at fixations using a retinal transform that provides realistic visual acuity by suitably degrading visual information in the periphery. In a task in which monkeys searched for a Gabor target in natural scenes, we characterized the relative importance of bottom-up and task-relevant influences by decoding fixated from nonfixated image patches based on visual features. At fast time scales, we found that search strategies can vary over the course of a single trial, with locations of higher saliency, target-similarity, edge–energy, and orientedness looked at later on in the trial. At slow time scales, we found that search strategies can be refined over several weeks of practice, and the influence of target orientation was significant only in the latter of two search tasks. Critically, these results were not observed without applying the retinal transform. Our results suggest that saccade-guidance strategies become apparent only when models take into account degraded visual representation in the periphery.
机译:像人类一样,猴子每秒会绕扫视3次。为了理解指导这一频繁决策的因素,视觉计算模型尝试使用自下而上的视觉功能和自上而下的目标来预测注视位置。这些因素的相对影响如何在多个时间尺度上演变?在这里,我们使用视网膜变换分析了固定处的视觉特征,该视网膜变换通过适当地降低周边的视觉信息来提供逼真的视敏度。在一项猴子在自然场景中搜索Gabor目标的任务中,我们通过解码基于视觉特征的非固定图像补丁中固定的图像,从而表征了自下而上和与任务相关的影响的相对重要性。在快速的时间尺度上,我们发现搜索策略在单个试验的过程中可能会有所不同,其显着性,目标相似性,边缘能量和定向性的位置将在试验的稍后阶段进行观察。在较慢的时间范围内,我们发现可以在数周的练习中完善搜索策略,而目标定向的影响仅在两个搜索任务中的后一个才有意义。至关重要的是,如果不应用视网膜转换,就不会观察到这些结果。我们的研究结果表明,只有在模型考虑到外围视力下降的情况下,扫视制导策略才变得明显。

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