LOCAL GABOR BINARY PATTERNS BASED ON MUTUAL INFORMATION FOR FACE RECOGNITION
LOCAL GABOR BINARY PATTERNS BASED ON MUTUAL INFORMATION FOR FACE RECOGNITION
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基于互信息的局部Gabor二值模式人脸识别
DOI：
10.1142/s021946780700291x
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发表时间：
2007-10-01
影响因子：
1.6
通讯作者：
Gao, Wen
中科院分区：
文献类型：
--
作者：
Zhang, Wenchao;Shan, Shiguang;Gao, Wen
合适的表示是人脸识别技术成功的关键之一。在本文中，我们提出了一种新的人脸表示方法，使用一个减少的局部直方图的局部Gabor二进制模式（LGBP）的基础上。在该方法中，人脸图像首先由LGBP直方图表示，从LGBP图像中提取。然后，选择具有高分离度和低相关性的局部LGBP直方图来获得降维的人脸描述符。大量的实验结果表明，该方法不仅大大降低了人脸表示的维数，但也优于最先进的人脸识别方法，如Fisherfaces，和Gabor Fisher分类（GFC）。
Appropriate representation is one of the keys to the success of face recognition technologies. In this paper, we present a novel face representation approach using a reduced set of local histograms based on Local Gabor Binary Patterns (LGBP). In the proposed method, a face image is first represented by the LGBP histograms which are extracted from the LGBP images. Then, the local LGBP histograms with high separability and low relevance are selected to obtain a dimension-reduced face descriptor. Extensive experimental results demonstrate that the proposed method not only greatly reduces the dimensionality of face representation, but also outperforms the state-of-theart approaches for face recognition, such as Fisherfaces, and Gabor Fisher Classification (GFC).