Author : Ham M. Rara
Publisher :
ISBN 13 :
Total Pages : 248 pages
Book Rating : 4.:/5 (144 download)
Book Synopsis Dimensionality Reduction Techniques in Face Recognition by : Ham M. Rara
Download or read book Dimensionality Reduction Techniques in Face Recognition written by Ham M. Rara and published by . This book was released on 2006 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: The direction of this work is in the field of subspace face recognition, where faces are assumed to belong to a face space, a subspace of the original high-dimensional space. The primary goal of this work is to present a qualitative and quantitative comparison of the three most representative subspace analysis algorithms in face recognition, namely: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Independent Component Analysis (ICA), and at the same time gain the necessary experience to apply and enhance these methods in the future, to achieve better recognition results. The motivation of this task is the lack of concrete comparison between the three algorithms in the face recognition literature. Results show that the PCA and ICA appear to be stable as the number of training images is increased, while the classification results of LDA become noticeably lower than the two former algorithms. The classification rates do not appear to be affected by the variation of subspace dimensions in the FERET experiments.