Face Descriptor of AdaBoost Patterns of Oriented Edge Magnitudes(APOEM)for Face Recognition

摘要：

　　This paper proposes a novel and efficient face descriptor,based on Patterns of Oriented Edge Magnitudes(POEM)features.AdaBoost is exploited to select optimally the most informative and discriminative features in each POEM image.Each face image is first represented by three POEM images,containing various significant features in different regions(sub-windows).The multi-class problem of face recognition is transformed into three independent two-class ones by classifying every two POEM images as intra-personal or extra-personal ones.The χ2 distance between corresponding POEM histograms of two POEM images is used as discriminative features.We optimize the parameters of APOEM and apply the whitened principal component analysis(WPCA)dimensionality reduction technique to get a lower dimension and more discriminative face descriptor.Experimental results on FERET and CAS-PEAL-R1 face databases demonstrate that the proposed method achieves better performance than the face descriptors based on WPCA-POEM and POEM.

关键词： AdaBoost POEM AdaBoost Patterns of Oriented Edge Magnitudes (APOEM) Whitened PCA Face Descriptor Face Recognition

作者: Ming Zeng Jianbo Su

作者单位: Department of Automation,Shanghai Jiao Tong University,Shanghai 200240

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 4899-4904

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）