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Face Recognition Based on a Single Training Image for Each Person Across Large Pose Variations
, M.Sc. Thesis Sharif University of Technology ; Manzuri-Shalmani, Mohammad Taghi (Supervisor)
Abstract
Most existing face recognition methods require several gallery (training) images per person for optimally training the system. On the other hand, in many real applications of face recognition such as law enforcement, driver’s license and identification by passport, generally only one image per person is available. However, “the variations between face images with different illumination and gestures are almost always larger than image variations due to change in face identity”, Therefore, in this thesis we have considered face recognition with changes in ambient lighting conditions and viewing angles where only one training image per person is availabe. A method have been proposed in which we...
A new image texture extraction algorithm based on Matching Pursuit Gabor wavelets
, Article 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05, Philadelphia, PA, 18 March 2005 through 23 March 2005 ; Volume II , 2005 , Pages II740-II744 ; 15206149 (ISSN); 0780388747 (ISBN); 9780780388741 (ISBN) ; Rabiee, H. R ; Ghanbari, M ; Shamsollahi, M. B ; Sharif University of Technology
2005
Abstract
Feature vector extraction, based on local image texture, is a primitive algorithm for many other applications, like segmentation, clustering and identification. If these feature vectors are a good match to the human visual system (HVS), we can expect to get the appropriate results by using them. Gabor filters has been used for this purpose successfully. In this paper we introduce a novel refinement, with the use of Matching Pursuit (MP) to improve the Gabor based texture feature extractor. With this improvement, we show that the separability of different textures will increase. Another consideration in this work is computation complexity. Therefore, we limit the basis function set to reduce...