Journal Paper

Paper Title - Using Eigenface Features to Drive Support Vector Machines in Face Recognition Systems


Abstract
Face recognition is one of the growing fields of research which has deep rooted applications in authentication domains. Its success can be attributed to the various algorithms which have strived to make it work in the real time. The major factor underlying such systems is the proper feature extraction and effective classification. The paper aims at using the two most well-known techniques to accomplish the above mentioned factors. They are Eigenface method -to extract features and Support vector Machines (SVM) –to classify the data. It was found that the proposed methodology was effective in terms of classification and due to the ease of implementation; it can be adopted in real-world applications.


Author - Sheela Shankar, V.R Udupi

Citation - Sheela Shankar   ,   V.R Udupi   ,   Sheela Shankar, V.R Udupi " Using Eigenface Features to Drive Support Vector Machines in Face Recognition Systems " , International Journal of Industrial Electronics and Electrical Engineering , Volume-2,Issue-11  ( Nov, 2014 )

Indexed - Google Scholar


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| Published on 2014-11-04