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Daniel Fiset, Caroline Blais, Ye Zhang, Kim Hébert, Frédéric Gosselin, Verena Willenbockel, Nicolas Dupuis-Roy, Daniel Bub, Qinglin Zhang, Jim Tanaka; Caucasian and Asian observers used the same visual features for race categorisation.. Journal of Vision 2012;12(9):32. doi: 10.1167/12.9.32.
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Using the Bubbles method (Gosselin & Schyns, 2001), we recently explored the visual information mediating race categorisation in Caucasian observers (Fiset et al., VSS 2008). Unsurprisingly, the results show that different visual features are essential to identifying the different races. More specifically, for African American faces, Caucasian participants used mainly the nose and the mouth in the spatial frequency (SF) bands ranging from 10 to 42 cycles per face width. For Asian faces, they used the eyes in the SF bands ranging from 10 to 84 cycles per face width and the mouth in the SF band ranging from 5 to 10 cycles per face width. For Caucasian faces, they used the eyes in the SF bands ranging from 5 to 21 cycles per face width as well as the mouth and the region between the eyes in the second highest SF band ranging from 21 to 42 cycles per face width. Here, we verify if the visual information subtending race categorisation differs for Asian participants. In order to do this, we asked 38 Asian participants from Southwest University in Chongqing (China) to categorise 700 "bubblized" faces randomly selected from sets of 100 male Caucasian faces, 100 male African American faces, and 100 male Asian faces. Separate multiple linear regressions between information samples and accuracy were performed for each race. The resulting classification images reveal the most important features for the categorisation of Caucasian, African American, and Asian faces by Asian observers. Comparison between observers of both races reveals nearly identical visual extraction strategies for race categorisation. These results will be discussed with respect to the literature showing differences in visual strategies employed by Asian and Caucasian observers (e.g. Blais et al., 2008).
Meeting abstract presented at VSS 2012
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