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Recognizing Human Gender in Computer Vision: A Survey

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PRICAI 2012: Trends in Artificial Intelligence (PRICAI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7458))

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Abstract

Gender is an important demographic attribute of people. This paper provides a survey of human gender recognition in computer vision. A review of approaches exploiting information from face and whole body (either from a still image or gait sequence) is presented. We highlight the challenges faced and survey the representative methods of these approaches. Based on the results, good performance have been achieved for datasets captured under controlled environments, but there is still much work that can be done to improve the robustness of gender recognition under real-life environments.

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Authors and Affiliations

  1. Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia

    Choon Boon Ng, Yong Haur Tay & Bok-Min Goi

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  1. Choon Boon Ng
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  2. Yong Haur Tay
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  3. Bok-Min Goi
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Editors and Affiliations

  1. Faculty of Environment, Society and Design, Department of Applied Computing, Lincoln University, P.O. Box 84, 7647, Christchurch, New Zealand

    Patricia Anthony

  2. School of Information Science and Technology, University of Tokyo, 7-3-1, Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan

    Mitsuru Ishizuka

  3. MIMOS Berhad, Knowledge Technology, Technology Park Malaysia,, 57000, Kuala Lumpur, Malaysia

    Dickson Lukose

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Ng, C.B., Tay, Y.H., Goi, BM. (2012). Recognizing Human Gender in Computer Vision: A Survey. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_31

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  • DOI: https://doi.org/10.1007/978-3-642-32695-0_31

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