The design of image-based soft-biometrics systems highly depends on the human factor analysis. How well can human do in gender/ethnicity recognition by looking at faces in different representations? How does human recognize gender/ethnicity? What factors affect the accuracy of gender/ethnicity recognition? The answers of these questions may inspire our design of computer-based automatic gender/ethnicity recognition algorithms. In this work, several subjective experiments are conducted to test the capability of human in gender/ethnicity recognition on different face representations, including 1D face silhouette, 2D face images and 3D face models. Our experimental results provide baselines and interesting inspirations for designing computer-based face gender/ethnicity recognition algorithms. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Hu, Y., Fu, Y., Tariq, U., & Huang, T. S. (2009). Subjective experiments on gender and ethnicity recognition from different face representations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5916 LNCS, pp. 66–75). https://doi.org/10.1007/978-3-642-11301-7_10
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