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Subjective Experiments on Gender and Ethnicity Recognition from Different Face Representations

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Advances in Multimedia Modeling (MMM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5916))

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Abstract

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.

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Hu, Y., Fu, Y., Tariq, U., Huang, T.S. (2010). Subjective Experiments on Gender and Ethnicity Recognition from Different Face Representations. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_10

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  • DOI: https://doi.org/10.1007/978-3-642-11301-7_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11300-0

  • Online ISBN: 978-3-642-11301-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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