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- Color provide an important clue for extracting the new color LBP histogram features for face recognition using Local Binary Pattern technique. To reduce redundancy RGB color space converted to YCbCr color space. The Local Binary Pattern is a non pa
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LBP已经成功应用于人脸检测,唇语识别,表情检测,动态纹理等等领域。其算法复杂度低,消耗内存小,原理简单.-LBP has been successfully applied to face detection, lip recognition, face detection, dynamic texture and so on. Its low algorithm complexity and memory consumption is small, simple principle.
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The ear, as a biometric, has been given less
attention, compared to other biometrics such as fingerprint,
face and iris. Since it is a relatively new biometric, no
commercial applications involving ear recognition are
available. Intensive
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LBP features of face recognition proposed
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这个是LBP人脸算法,对学习者有很好的帮助,关于人脸表情识别,这里是基于ORL人脸库。-This is the human face LBP algorithm, the learners have good help, on facial expression recognition, here is based on the ORL database.
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LBP算法的C++实现,对于做表情识别特征提取很有帮助-LBP algorithm C++ implementation, very helpful for face recognition feature extraction
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基于Haar特征的LBP算法,在人脸识别方面会更加迅速,而且识别率很高-LBP algorithm based on Haar features in face recognition will be more rapid, and high recognition rate
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为了实现复杂环境下的人脸特征有效表达,提出一种改进的梯度方向直方图(HOG)人脸识别方法.首先以人脸图像网格作为采样窗口并在其上提取 HOG特征;然后将所有网格 HOG特征向量进行组合,实现整个人脸特
征表达;最后采用最近邻分类器进行识别.另外,比较了该方法与Gabor小波和局部二值模式(LBP)2种著名的人脸
局部特征表示方法的优劣.实验结果表明,在调优的 HOG参数下,在具有光照和时间环境等复杂变化的FERET人
脸库中,较少维数的 HOG特征比LBP特征有更好的表现,而且 HO
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关于模式识别的参考文献,有LBP(局部二值模式),BLBP(多尺度二值模式),MBE-LBP等多种算法,可以看考一下,里面的内容是有关于人脸的识别。-References about pattern recognition, with LBP (local binary pattern), BLBP (multi-scale binary mode), MBE- LBP and other algorithm, can look to take an examination of, it is
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face recognition using lbp ltp and gabor features code
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face recognition code using lbp ltp features
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局部二值模式(LBP),用于人脸识别局部文理特征的提取-Local binary pattern( LBP), local arts and feature extraction for Face Recognition
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局部多值模式LMP,对lbp的改进算法,用于人脸识别局部文理特征的提取-
Partial multiple- valued model LMP, improvements to the LBP algorithm for Face Recognition Feature extraction of local arts and sciences
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是对jaffe人脸库进行识别测试的主程序,将jaffe人脸库分为训练集和测试集两部分,首先对图片进行LBP+LPQ特征提取,然后svm分类识别,统计识别率
-Is jaffe face recognition test the main library, the library will jaffe face divided into training and test sets of two parts, the first of LBP+LPQ image feature extrac
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人脸识别系统采用了LBP PCA 2CKPCA 2BSVM算法实现的,效率高。-Face Recognition System using LBP PCA 2B KPCA 2B SVM algorithm, and high efficiency.
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LBP作为一种人脸识别技术,改程序是将其用C语言代码实现并进行封装-LBP as a face recognition technology, the reform process is to use C language code and encapsulate
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代码分为两部分,训练和测试,1、将训练图像的地址保存在taining_set.txt文件中,2、分别对训练图像进行预处理和特征提取,提取图像的LBP纹理图,再使用PCA方法进行降维。3、使用cvSVN进行分类-Face recognition
The code is divided into two parts, training and testing, 1, the training image is stored in the taining_set.txt file, 2, resp
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本程序中,利用了LBP特征对人脸特征进行提取,并且利用SVM对提取的人脸特征进行训练和识别,其中,所用的图像处理库OpenCV2.4.9版本;通过对人脸库中的标准标本进行测试,算法识别率高达95%以上;(LBP features extract facial features, and use SVM to extract and recognize the facial features. The OpenCV2.4.9 version of the image processing libr
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基于LBP特征的人脸识别,还有很多地方不够完善,多担待(Face recognition based on LBP features)
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基于lbp实现人脸识别,使用matlab实现,代码简单易懂(Realization of face recognition)
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