Gaze Control during Scene Viewing: Behavioral and Computational Approaches

当我们观看视觉世界时，我们的眼睛每秒大约三次从一个位置飞到另一个位置，这种运动被称为扫视。有用的视觉信息只有在凝视时才能获得，凝视是凝视对象或场景特征的短暂时间段。在场景中实时引导眼跳和凝视的认知和神经过程属于“凝视控制”这个术语。这个项目专注于解开人类凝视控制在活跃的真实世界场景感知中是如何运作的。这个项目从理解眼睛运动的时间安排将提供对控制凝视的潜在认知和神经系统的关键洞察开始，接近人类凝视控制。这项研究将创新的眼球跟踪方法与模拟眼动控制的工作计算模型结合在一起。在这个研究项目中，经验和计算线索是互补和协同的。一方面，我们可以通过确定模型是否能产生看起来像人类产生的眼动来测试我们对凝视控制的理解。另一方面，来自该模型的洞察力可以作为一种工具来增强我们对凝视控制的理论理解，这些洞察力可以通过新的实验进一步检验。该项目的结果将加强对人类如何感知和理解视觉世界的基本科学理解。该项目还对创造可以通过眼球运动控制的新显示技术和机器界面产生了广泛的影响。研究结果对设计新的人工视觉系统具有重要意义，这种系统可以主动跟踪和关注环境中的相关信息。

When we view the visual world, our eyes flit from one location to another about three times per second, in movements called saccades. Useful visual information is acquired only during fixations, brief periods of time when gaze rests on an object or scene feature. The cognitive and neural processes that direct saccades and fixations through a scene in real time fall under the term 'gaze control'. This project focuses on unraveling how human gaze control operates during active real-world scene perception. This project approaches human gaze control by starting with the insight that understanding eye movement timing will provide key insight into the underlying cognitive and neural systems that control gaze. The research combines innovative eye-tracking methods with a working computational model that simulates eye movement control. In this research program, the empirical and computational threads are complementary and synergistic. On the one hand, we can test our understanding of gaze control by determining whether the model can produce eye movements that look like those produced by people. On the other hand, insights from the model can be used as a tool to enhance our theoretical understanding of gaze control, and these insights can be further tested with new experiments. The results from this project will enhance basic scientific understanding of how humans perceive and understand the visual world. The project also has wide-ranging implications for the creation of new display technologies and machine interfaces that can be controlled by eye movements. And the results are relevant for the design of new artificial vision systems that actively track and focus on relevant information in the environment.