2013Electronic Design EngineeringRequires access

Face recognition based on multi-kernel support vector machine

Lifeng Zhao

Open publisher page 1 citations

Abstract

This paper researches the selection problem of kernel function and the parameters optimization problem Support Vector Machine(SVM).Through the features of local kernel function and global kernel function,we mix the Gaussian kernel function and polynomial kernel function together and propose a new kernel function named multi-kernel function.Then we apply Multi-kernel function into face recognition and prove that multi-kernel function can achieve a higher recognition rate.

About this research paper

What this paper is about

This paper researches the selection problem of kernel function and the parameters optimization problem Support Vector Machine(SVM).Through the features of local kernel function and global kernel function,we mix the Gaussian kernel function and polynomial kernel function together and propose a new kernel function named multi-kernel function.Then we apply Multi-kernel function into face recognition and prove that multi-kernel function can achieve a higher recognition rate.

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Available abstract

This paper researches the selection problem of kernel function and the parameters optimization problem Support Vector Machine(SVM).Through the features of local kernel function and global kernel function,we mix the Gaussian kernel function and polynomial kernel function together and propose a new kernel function named multi-kernel function.Then we apply Multi-kernel function into face recognition and prove that multi-kernel function can achieve a higher recognition rate.

Key concepts: Polynomial kernel, Radial basis function kernel, Kernel (algebra), Kernel method, Kernel embedding of distributions, Variable kernel density estimation, Gaussian function, String kernel

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