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Multispectral Local Binary Pattern Histogram for Component-based Color Face Verification

机译:基于组件的颜色面验证的多光谱局部二进制图案直方图

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A novel discriminative face representation derived by the Linear Discriminant Analysis (LDA) of multispectral Local binary pattern histograms is proposed for color face recognition. The color face image is first photometricly normalized and partitioned into several non-overlapping regions. In each region, multispectral local binary pattern histograms are extracted and concatenated into a regional feature. The feature is then projected into a LDA space to be used as a regional discriminative facial descriptor. The overall similarity score is obtained by fusing the similarity scores of the regional descriptors. The method is implemented and tested in face verification on the XM2VTS and FRGC 2.0 databases with very promising results.
机译:提出了一种由多光谱局部二进制图案直方图的线性判别分析(LDA)来源的新颖鉴别面,用于颜色面部识别。彩色面部图像首先将光度归一化并分成几个非重叠区域。在每个区域中,提取多光谱局部二进制模式直方图并将其连接到区域特征中。然后将该功能投影到LDA空间中以用作区域鉴别的面部描述符。通过融合区域描述符的相似度分数来获得整体相似度分数。该方法在XM2VTS和FRGC 2.0数据库上验证和测试,具有非常有前途的结果。

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