Expert Face Recognition: The Influence of Experience

专家人脸识别：经验的影响

• 批准号: RGPIN-2016-04281
• 负责人: Mondloch, Catherine
• 金额: $ 2.99万
• 依托单位: Brock University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=631089
• 关键词: Expert; Face; Recognition; Influence; Experience

Two pictures of the same person can look very different and pictures of two different people can look very similar. Thus, accurate face recognition requires both discrimination (telling people apart) and identity matching (recognizing a person when his/her appearance changes). The objective of my research is to understand the mechanisms underlying the development of expert face recognition across the lifespan. To do so, I take two approaches. First, I examine how face recognition and the underlying mechanisms change across the lifespan (e.g., as children encounter an increasing number of new faces and during old age). Second, I compare adults’ ability to recognize identity in faces from categories with which they have abundant (e.g., own-race, young adult) vs. minimal (other-race, older adult) experience. I propose doing so using three approaches. The first focuses on a largely ignored challenge: Recognizing a face despite natural variability in appearance (changes in hairstyle, makeup, viewpoint). This is the challenge faced by passport officers and an ability that allows us to recognize our neighbour when she dons new glasses. Doing so is difficult when faces are unfamiliar, especially for children and for adults viewing other-race faces. I will investigate the process by which a face becomes sufficiently familiar to allow such recognition and how that process changes across the lifespan and differs across face categories. The second focuses on whether reliance on two cues to facial identity—face shape and face texture—varies as a function of familiarity, perceiver age, and face category. Adults rely on face shape (feature shape and spacing) to learn new own-race faces but face texture (skin tone) to recognize them, a pattern most evident in good recognizers. I will manipulate the salience of shape versus texture cues to examine whether age-related differences in face recognition can be attributed to reduced sensitivity to face shape during learning and/or a failure to rely on texture as a face becomes familiar. I will conduct a parallel study to examine whether the same pattern might underlie poor recognition of other-race/age faces. The third project focuses on how limitations in visual working memory affect face recognition. Learning a new face requires the perceiver to store separate instances and/or to build an average; both mechanisms require the observer to encode a face, an ability that is reflected in visual working memory. I will measure the capacity and precision of working memory and compare these across age groups (children, young adults, older adults) and face categories (e.g., young vs. older adult faces; own- vs. other-race faces). Together, the results will provide novel insights about how face perception becomes finely tuned to environmental input across the lifespan.

同一个人的两张照片可能看起来非常不同，两个不同的人的照片可能看起来非常相似。因此，准确的人脸识别需要区分（区分人）和身份匹配（当他/她的外表发生变化时识别人）。我研究的目的是了解专家面部识别在整个生命周期中发展的机制。为此，我采取两种方法。首先，我研究了人脸识别和潜在机制在整个生命周期中的变化（例如，随着孩子们遇到越来越多的新面孔和老年人）。其次，我比较了成年人从他们拥有丰富的类别中识别面孔身份的能力（例如，本族，年轻人）与最小（其他种族，老年人）的经验。我建议采用三种方法。第一个重点是一个很大程度上被忽视的挑战：识别一张脸，尽管外表有自然的变化（发型，化妆，观点的变化）。这是护照官员面临的挑战，也是一种让我们在邻居戴上新眼镜时认出她的能力。当面孔不熟悉时，这样做很困难，特别是对于儿童和成年人来说，他们看到的是其他种族的面孔。我将研究一张脸变得足够熟悉以允许这种识别的过程，以及这个过程在整个生命周期中如何变化，以及在不同的面孔类别中如何不同。第二个重点是是否依赖于两个线索的面部身份，面部形状和面部纹理的熟悉程度，感知者年龄和面部类别的功能而变化。成年人依靠面部形状（特征形状和间距）来学习新的本族面孔，但面部纹理（肤色）来识别它们，这在良好的识别者中最为明显。我将操纵形状与纹理线索的显着性，以检查是否年龄相关的差异，在面部识别可以归因于减少敏感性的面部形状在学习和/或未能依赖于纹理，因为一张脸变得熟悉。我将进行一项平行研究，以检查是否相同的模式可能导致对其他种族/年龄面孔的识别不良。第三个项目关注视觉工作记忆的局限性如何影响人脸识别。学习一张新面孔需要感知者存储单独的实例和/或建立一个平均值;这两种机制都需要观察者对面孔进行编码，这种能力反映在视觉工作记忆中。我将测量工作记忆的容量和精确度，并在不同年龄组（儿童、年轻人、老年人）和面孔类别（例如，年轻人与年长的成年人的面孔;自己的面孔与其他种族的面孔）。总之，这些结果将提供关于面部感知如何在整个生命周期中与环境输入进行微调的新见解。