Borjon Jeremy I, Schroer Sara E, Bambach Sven, Slone Lauren K, Abney Drew H, Crandall David J, Smith Linda B
Department of Psychological and Brain Sciences, Indiana University;
School of Informatics, Computing, and Engineering, Indiana University.
J Vis Exp. 2018 Oct 5(140):58445. doi: 10.3791/58445.
Infants and toddlers view the world, at a basic sensory level, in a fundamentally different way from their parents. This is largely due to biological constraints: infants possess different body proportions than their parents and the ability to control their own head movements is less developed. Such constraints limit the visual input available. This protocol aims to provide guiding principles for researchers using head-mounted cameras to understand the changing visual input experienced by the developing infant. Successful use of this protocol will allow researchers to design and execute studies of the developing child's visual environment set in the home or laboratory. From this method, researchers can compile an aggregate view of all the possible items in a child's field of view. This method does not directly measure exactly what the child is looking at. By combining this approach with machine learning, computer vision algorithms, and hand-coding, researchers can produce a high-density dataset to illustrate the changing visual ecology of the developing infant.
婴儿和幼儿在基本感官层面上看待世界的方式与他们的父母有着根本的不同。这在很大程度上是由于生物学上的限制：婴儿的身体比例与父母不同，并且他们控制头部运动的能力发育得较差。这些限制会限制可用的视觉输入。本方案旨在为使用头戴式摄像头的研究人员提供指导原则，以了解发育中的婴儿所经历的不断变化的视觉输入。成功使用本方案将使研究人员能够设计并开展关于在家中或实验室环境下发育中儿童视觉环境的研究。通过这种方法，研究人员可以汇总儿童视野中所有可能物品的总体视图。此方法并不直接精确测量儿童正在注视的内容。通过将这种方法与机器学习、计算机视觉算法和人工编码相结合，研究人员可以生成一个高密度数据集，以说明发育中婴儿不断变化的视觉生态。
