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Benjamin Balas; Children's use of visual summary statistics for material categorization. Journal of Vision 2017;17(12):22. doi: https://doi.org/10.1167/17.12.22.
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© ARVO (1962-2015); The Authors (2016-present)
Although adults' ability to recognize materials from complex natural images has been well characterized, we still know very little about the development of material perception. When do children exhibit adult-like abilities to categorize materials? What visual features do they use to do so as a function of age and material category? In the present study, we attempted to address both of these issues in two experiments that we administered to school-age children (5–10 years old) and adults. In both tasks, we asked our participants to categorize natural materials (metal, stone, water, and wood) using original images of these materials as well as synthetic images made with the Portilla–Simoncelli algorithm. By including synthetic images in our stimulus set, we were able to assess both how material categorization develops during childhood and how visual summary statistics are recruited for material perception across age groups. We observed that when asked to provide category labels for individual images (Experiment 1), young children were disproportionately bad at categorizing some materials after they were synthesized, suggesting material-specific changes in information use over the course of development. However, when asked to match real and synthetic images according to material category without labeling (Experiment 2), these effects were weakened. We conclude that while children have adult-like abilities to encode and compare images based on summary statistics, the mapping between summary statistics and category labels undergoes prolonged development during childhood.
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