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A Study on Gait-Based Gender Classification
Yu, Shiqi1,2; Tan, Tieniu1; Huang, Kaiqi1; Jia, Kui2; Wu, Xinyu2
Source PublicationIEEE TRANSACTIONS ON IMAGE PROCESSING
2009-08-01
Volume18Issue:8Pages:1905-1910
SubtypeArticle
AbstractGender is an important cue in social activities. In this correspondence, we present a study and analysis of gender classification based on human gait. Psychological experiments were carried out. These experiments showed that humans can recognize gender based on gait information, and that contributions of different body components vary. The prior knowledge extracted from the psychological experiments can be combined with an automatic method to further improve classification accuracy. The proposed method which combines human knowledge achieves higher performance than some other methods, and is even more accurate than human observers. We also present a numerical analysis of the contributions of different human components, which shows that head and hair, back, chest and thigh are more discriminative than other components. We also did challenging cross-race experiments that used Asian gait data to classify the gender of Europeans, and vice versa. Encouraging results were obtained. All the above prove that gait-based gender classification is feasible in controlled environments. In real applications, it still suffers from many difficulties, such as view variation, clothing and shoes changes, or carrying objects. We analyze the difficulties and suggest some possible solutions.
KeywordAppearance-based Features Gait Analysis Gender Classification Human Silhouette
WOS HeadingsScience & Technology ; Technology
WOS KeywordRECOGNITION
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000268033300019
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3766
Collection智能感知与计算研究中心
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
2.CAS CUHK, Shenzhen Inst Adv Integrat Technol, Shenzhen 518067, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yu, Shiqi,Tan, Tieniu,Huang, Kaiqi,et al. A Study on Gait-Based Gender Classification[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2009,18(8):1905-1910.
APA Yu, Shiqi,Tan, Tieniu,Huang, Kaiqi,Jia, Kui,&Wu, Xinyu.(2009).A Study on Gait-Based Gender Classification.IEEE TRANSACTIONS ON IMAGE PROCESSING,18(8),1905-1910.
MLA Yu, Shiqi,et al."A Study on Gait-Based Gender Classification".IEEE TRANSACTIONS ON IMAGE PROCESSING 18.8(2009):1905-1910.
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