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Contextual Guidance of Eye Movements and Attention in Real-World Scenes: The Role of Global Features in Object Search

机译:现实世界中眼睛运动和注意力的上下文指导:对象搜索中全局特征的作用

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摘要

Many experiments have shown that the human visual system makes extensive use of contextual information for facilitating object search in natural scenes. However, the question of how to formally model contextual influences is still open. On the basis of a Bayesian framework, the authors present an original approach of attentional guidance by global scene context. The model comprises 2 parallel pathways; one pathway computes local features (saliency) and the other computes global (scene-centered) features. The contextual guidance model of attention combines bottom-up saliency, scene context, and top-down mechanisms at an early stage of visual processing and predicts the image regions likely to be fixated by human observers performing natural search tasks in real-world scenes. eye movements, visual search, context, global feature, Bayesian model
机译:许多实验表明,人类视觉系统广泛使用了上下文信息来促进自然场景中的对象搜索。但是,如何正式建模上下文影响的问题仍然存在。在贝叶斯框架的基础上,作者提出了一种通过全局场景上下文进行注意力指导的原始方法。该模型包括2条平行路径;一种途径计算局部特征(显着性),另一种途径计算全局(以场景为中心)特征。注意的上下文指导模型在视觉处理的早期阶段结合了自下而上的显着性,场景上下文和自上而下的机制,并预测了在现实世界场景中执行自然搜索任务的人类观察者可能会固定的图像区域。眼动,视觉搜索,上下文,全局特征,贝叶斯模型

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