Gaze Control during Scene Viewing: Behavioral and Computational Approaches

当我们观看视觉世界时，我们的眼睛每秒从一个位置飞到另一个位置大约三次，这种运动称为扫视。有用的视觉信息仅在注视期间获得，注视停留在物体或场景特征上的短暂时间段。在真实的时间内引导扫视和注视通过场景的认知和神经过程属于术语“注视控制”。该项目的重点是揭示人类的视线控制如何在主动现实世界场景感知过程中运作。该项目通过了解眼球运动时间将为控制凝视的潜在认知和神经系统提供关键见解，从而开始研究人类的凝视控制。该研究将创新的眼动跟踪方法与模拟眼动控制的工作计算模型相结合。在这个研究项目中，经验和计算线程是互补和协同的。一方面，我们可以通过确定模型是否可以产生看起来像人产生的眼球运动来测试我们对凝视控制的理解。另一方面，来自模型的见解可以作为一种工具来增强我们对凝视控制的理论理解，这些见解可以通过新的实验进一步测试。该项目的结果将增强对人类如何感知和理解视觉世界的基本科学理解。该项目还对创造新的显示技术和可以通过眼球运动控制的机器界面产生了广泛的影响。这些结果对于设计新的人工视觉系统具有重要意义，这些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.