Ethnicity classification based on fusion of face and gait

	Ethnicity classification based on fusion of face and gait
	De Zhang; Yunhong Wang; Zhaoxiang Zhang; Maodi Hu
	2012-03-29
会议日期	March 29 – April 1 2012
会议地点	New Delhi, India
关键词	Face Feature Extraction Databases Support Vector Machines Cameras Vectors Legged Locomotion
英文摘要	The recognition of ethnicity of an individual can be very useful in a video-based surveillance system. In this paper, we propose a multimodal biometric system involving an integration of frontal face and lateral gait, for the specific problem of ethnicity classification. This system performs a feature fusion to improve the discrimination of human ethnicity. Face features are extracted by means of the uniform LBP operator and gait information is characterized by a spatio-temporal representation. Afterwards, canonical correlation analysis (CCA), as a powerful tool to relate two sets of measurements, is used to fuse the two modalities at the feature level. A database including 36 walking people from East Asia and South America is built for the purpose of ethnicity classification. The experimental results show that the ethnicity recognition rate is improved by fusing face and gait information.
会议录	ICB 2012
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/13271]
专题	自动化研究所_类脑智能研究中心
通讯作者	Zhaoxiang Zhang
推荐引用方式 GB/T 7714	De Zhang,Yunhong Wang,Zhaoxiang Zhang,et al. Ethnicity classification based on fusion of face and gait[C]. 见:. New Delhi, India. March 29 – April 1 2012.