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Full-Text Articles in Physical Sciences and Mathematics
Learning Local Features Using Boosted Trees For Face Recognition, Rajkiran Gottumukkal
Learning Local Features Using Boosted Trees For Face Recognition, Rajkiran Gottumukkal
Electrical & Computer Engineering Theses & Dissertations
Face recognition is fundamental to a number of significant applications that include but not limited to video surveillance and content based image retrieval. Some of the challenges which make this task difficult are variations in faces due to changes in pose, illumination and deformation. This dissertation proposes a face recognition system to overcome these difficulties. We propose methods for different stages of face recognition which will make the system more robust to these variations. We propose a novel method to perform skin segmentation which is fast and able to perform well under different illumination conditions. We also propose a method …
3d Face Reconstruction From Limited Images Based On Differential Evolution, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Andrew G. Tescher (Ed.)
3d Face Reconstruction From Limited Images Based On Differential Evolution, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Andrew G. Tescher (Ed.)
Electrical & Computer Engineering Faculty Publications
3D face modeling has been one of the greatest challenges for researchers in computer graphics for many years. Various methods have been used to model the shape and texture of faces under varying illumination and pose conditions from a single given image. In this paper, we propose a novel method for the 3D face synthesis and reconstruction by using a simple and efficient global optimizer. A 3D-2D matching algorithm which employs the integration of the 3D morphable model (3DMM) and the differential evolution (DE) algorithm is addressed. In 3DMM, the estimation process of fitting shape and texture information into 2D …
2d Face Database Diversification Based On 3d Face Modeling, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Manuel Filipe Costa (Ed.)
2d Face Database Diversification Based On 3d Face Modeling, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Manuel Filipe Costa (Ed.)
Electrical & Computer Engineering Faculty Publications
Pose and illumination are identified as major problems in 2D face recognition (FR). It has been theoretically proven that the more diversified instances in the training phase, the more accurate and adaptable the FR system appears to be. Based on this common awareness, researchers have developed a large number of photographic face databases to meet the demand for data training purposes. In this paper, we propose a novel scheme for 2D face database diversification based on 3D face modeling and computer graphics techniques, which supplies augmented variances of pose and illumination. Based on the existing samples from identical individuals of …
Co-Occurrence Matrix And Its Statistical Features As A New Approach For Face Recognition, Alaa Eleyan, Hasan Demirel
Co-Occurrence Matrix And Its Statistical Features As A New Approach For Face Recognition, Alaa Eleyan, Hasan Demirel
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a new face recognition technique is introduced based on the gray-level co-occurrence matrix (GLCM). GLCM represents the distributions of the intensities and the information about relative positions of neighboring pixels of an image. We proposed two methods to extract feature vectors using GLCM for face classification. The first method extracts the well-known Haralick features from the GLCM, and the second method directly uses GLCM by converting the matrix into a vector that can be used in the classification process. The results demonstrate that the second method, which uses GLCM directly, is superior to the first method that …
An Algorithm To Minimize Within-Class Scatter And To Reduce Common Matrix Dimension For Image Recognition, Ümi̇t Çi̇ğdem Turhal, Alpaslan Duysak
An Algorithm To Minimize Within-Class Scatter And To Reduce Common Matrix Dimension For Image Recognition, Ümi̇t Çi̇ğdem Turhal, Alpaslan Duysak
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a new algorithm using 2DPCA and Gram-Schmidt Orthogonalization Procedure for recognition of face images is proposed. The algorithm consists of two parts. In the first part, a common feature matrix is obtained; and in the second part, the dimension of the common feature matrix is reduced. Resulting common feature matrix with reduced dimension is used for face recognition. Column and row covariance matrices are obtained by applying 2DPCA on the column and row vectors of images, respectively. The algorithm then applies eigenvalue-eigenvector decomposition to each of these two covariance matrices. Total scatter maximization is achieved taking the …