How do children's visual concepts change across childhood, and how might these changes be reflected in their drawings? Here we investigate developmental changes in children’s ability to emphasize the relevant visual distinctions between object categories in their drawings. We collected over 13K drawings from children aged 2-10 years via a free-standing drawing station in a children's museum. We hypothesized that older children would produce more recognizable drawings, and that this gain in recognizability would not be entirely explained by concurrent development in visuomotor control. To measure recognizability, we applied a pretrained deep convolutional neural network model to extract a high-level feature representation of all drawings, and then trained a multi-way linear classifier on these features. To measure visuomotor control, we developed an automated procedure to measure their ability to accurately trace complex shapes. We found consistent gains in the recognizability of drawings across ages that were not fully explained by children's ability to accurately trace complex shapes. Furthermore, these gains were accompanied by an increase in how distinct different object categories were in feature space. Overall, these results demonstrate that children's drawings include more distinctive visual features as they grow older.
How do children's visual concepts change across childhood, and how might these changes be reflected in their drawings? Here we investigate developmental changes in children's ability to emphasize the relevant visual distinctions between object categories in their drawings. We collected over 13K drawings from children aged 2-10 years via a free-standing drawing station in a children's museum. We hypothesized that older children would produce more recognizable drawings, and that this gain in recognizability would not be entirely explained by concurrent development in visuomotor control. To measure recognizability, we applied a pretrained deep convolutional neural network model to extract a high-level feature representation of all drawings, and then trained a multi-way linear classifier on these features. To measure visuomotor control, we developed an automated procedure to measure their ability to accurately trace complex shapes. We found consistent gains in the recognizability of drawings across ages that were not fully explained by children's ability to accurately trace complex shapes. Furthermore, these gains were accompanied by an increase in how distinct different object categories were in feature space. Overall, these results demonstrate that children's drawings include more distinctive visual features as they grow older.
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