Face Recognition Dimensionality Reduction Based on LLE and ISOMAP
Local linear embedding (LLE) and isometric feature mapping (ISOMAP) are two basic patterns of nonlinear dimensionality reduction. Their respective strengths and weaknesses in face recognition deserve deep-going comparative study. Therefore, this paper is to test the two patterns’ performance efficiency in different parameters, analyze and summarize the two dimensionality reduction pattern’s characteristics and scope of application, apply LLE and main constituent analysis into face recognition and summarize probability of detection of face recognition.
KeywordsNonlinear dimensionality reduction Local linear embedding Isometric mapping Face recognition
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