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The human brain seems to care a lot about faces. It’s dedicated a specific area to identifying them, and the neurons there are so good at their job that most of us can readily recognize thousands of i...
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension. It has been used widely in many applications involving high-dimensional data, such as face recognition, ...
In this paper, a new face recognition technique is introduced based on the gray-level co-occurrence matrix (GLCM). GLCM represents the distributions of the intensities and the information about relati...
We present symbolic kernel discriminant analysis (symbolic KDA) for face recognition in the framework of symbolic data analysis. Classical KDA extracts features, which are single-valued in nature to r...
人脸识别软件首先通过对每一个对象的3~10幅脸像的训练来认识该对象,并把该对象的人脸参数存储到人脸数据库中,然后可以用来识别其他的脸像。系统的技术特点如下:系统对表情变化、比例变化具有较好鲁棒性,能够识别40度以内的侧面脸像,对适度光照变化具有一定鲁棒性;系统用数学模型的参数表征人脸特征,数据库中不用保留训练图像样本,人脸模型和训练样本可以分离;系统根据待识别脸像与数据库中对象的匹配的似然度,给出...
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Machine with the Kernel ...
This paper proposes the AdaBoost Gabor Fisher Classifier (AGFC) for robust f ace recognition, in which a chain AdaBoost learning method based on Bootstrap re-sampling is proposed and applied to face r...
This paper introduces a novel discriminant moment-based method as a feature extraction technique for face recognition. In this method, pseudo Zernike moments are performed before the application of Fi...
The performances of the current face r ecognition systems suffer heavily from the variations in lighting. To deal with this problem, this paper presents an illumination normaliza tion approach by rel...

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