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SVM Kernel Design Using Local Feature Analysis  

Lee, Il-Yong (LG전자 전자기술원 정보기술 연구소)
Ahn, Jung-Ho (강남대학교 컴퓨터미디어정보공학부)
Publication Information
Journal of Digital Contents Society / v.11, no.1, 2010 , pp. 17-24 More about this Journal
Abstract
The purpose of this study is to design and implement a kernel for the support vector machine(SVM) to improve the performance of face recognition. Local feature analysis(LFA) has been well known for its good performance. SVM kernel plays a limited role of mapping low dimensional face features to high dimensional feature space but the proposed kernel using LFA is designed for face recognition purpose. Because of the novel method that local face information is extracted from training set and combined into the kernel, this method is expected to apply to various object recognition/detection tasks. The experimental results shows its improved performance.
Keywords
SVM;
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