Seeing the forest and the trees: Cognitive and neural mechanisms underlying recognition of individual objects and sets

当面对一组相似的对象时，例如一群人脸或迎面而来的车流，人类观察者可以快速且似乎自动地提取这些对象组的汇总统计信息(例如，平均表情或位置)。这项研究将为人类视觉系统如何执行这一巨大的计算壮举提供洞察力。这代表着在总体上理解视觉以及最终将我们的知识应用于人工视觉系统的开发和视觉障碍的康复方面迈出的关键一步。这项研究还将调查注意力负荷对感知环境汇总统计数据的影响，这对于在繁忙的交通中驾驶等任务至关重要。

When confronted with a set of similar objects, such as a crowd of faces or a flow of oncoming cars, human observers can rapidly and seemingly automatically extract summary statistics of these sets of objects (e.g., mean expression or location). This research will provide insights into how the human visual system executes this massive feat of computation. This represents a vital step in understanding vision in general and in eventually applying our knowledge to the development of artificial vision systems and to rehabilitation of visual disorders. The research will also investigate the effects of attentional load on perception of summary statistics of the environment, which is critical for tasks such as driving in busy traffic.