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Local-Gravity-Face (LG-face) for Illumination-Invariant and Heterogeneous Face Recognition

机译:局部重力人脸(LG人脸)用于照明不变和异构人脸识别

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摘要

This paper proposes a novel method called local-gravity-face () for illumination-invariant and heterogeneous face recognition (HFR). employs a concept called the local gravitational force angle (). The is the direction of the gravitational force that the center pixel exerts on the other pixels within a local neighborhood. A theoretical analysis shows that the is an illumination-invariant feature, considering only the reflectance part of the local texture effect of the neighboring pixels. It also preserves edge information. Rank 1 recognition rates of 97.78% on the CMU-PIE database and 97.31% on the Extended Yale B database are achieved under varying illumination, demonstrating that is an effective method of illumination-invariant face recognition. For HFR, when faces appear in different modalities, produces a common feature representation. Rank 1 recognition rates of 99.96% on the CUFS database, 98.67% on the CUFSF database, and 99.78% on the CASIA-HFB database show that the is also an effective method for HFR. The proposed method also performs consistently in the presence of complicated variations and noise.
机译:本文提出了一种新的方法,称为局部重力人脸()用于照明不变和异构人脸识别(HFR)。采用了称为局部重力角()的概念。是中心像素施加在局部邻域内其他像素上的重力的方向。理论分析表明,仅考虑相邻像素的局部纹理效果的反射率部分,它是照明不变的特征。它还保留边缘信息。在变化的光照条件下,在CMU-PIE数据库上的1级识别率达到97.78%,在扩展Yale B数据库上达到97.31%,这表明该方法是不变光照的有效面部识别方法。对于HFR,当面以不同的形式出现时,会生成一个通用的特征表示。在CUFS数据库上的1级识别率为99.96%,在CUFSF数据库上的识别率为98.67%,在CASIA-HFB数据库上的识别率为99.78%,这表明HFR也是一种有效的HFR方法。所提出的方法在存在复杂变化和噪声的情况下也能一致地执行。

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