Work

The Role of Spatial Frequency Information in Face Classification by Race

Year: 2017

Type: article

Abstract: It was found that face classification by race is more quickly for other-race than own-race faces (other-race classification advantage, ORCA). Controlling the spatial frequencies of face images, the current study investigated the perceptual processing differences based on spatial frequencies between own-race and other-race faces that might account for the ORCA. Regardless of the races of the observers, the own-race faces were classified faster and more accurately for broad-band faces than for both lower and higher spatial frequency (SF) faces, whereas, although other-race faces were classified less accurately for higher SF than for either broad-band or lower SF faces, there was no difference between broad-band and lower SF conditions of other-race faces. Although it was not evident for higher SF condition, the ORCA was more evident for lower SF than that for broad-band faces. The present data indicate that global/configural information is needed for subordinate race categorization of faces and that an important source of ORCA is application of global/configural computations by default while categorizing an own-race face but not while categorizing an other-race face.

Source: Frontiers in Psychology

DOI: 10.3389/fpsyg.2017.01152

Authors: Guoping Zhang, Zeyao Wang, Jie Wu, Lun Zhao

Institutions: Peking University, Nankai University, Michigan State University, Tianjin Normal University

Language: English

Topic: Face Recognition and Perception

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,801

Funders: Harvard University, National Natural Science Foundation of China, China Scholarship Council