Recognizing human gender in computer vision: a survey

Authors:
Choon Boon Ng;Yong Haur Tay;Bok-Min Goi
Affiliations:
Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia;Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia;Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia
Venue:
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Year:
2012

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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.