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While features used for texture analysis have been successfully used in some biometric applications, only quite few works have considered them in facial image analysis. Texture-based region descriptors can be very useful in recognizing faces and facial expressions, detecting faces and different facial components, and in other face related tasks. This paper demonstrates this issue by considering the...
Active Shape Model (ASM) has been recognized as one of the typical methods for image understanding. Simply speaking, it iterates two steps: profile-based landmarks local searching, and statistics-based global shape modeling. We argue that the simple 1D profile matching may not localize landmarks accurately enough, and the unreliable localized landmarks will mislead the following shape matching. Considering...
This paper proposes a new method for personal identity verification based the analysis of face images applying One Class Support Vector Machines. This is a recently introduced kernel method to build a unary classifier to be trained by using only positive examples, avoiding the sensible choice of the impostor set typical of standard binary Support Vector Machines. The features of this classifier and...
The problem of illumination makes the face recognition still an unsolved problem. A new normalization method was presented which is illumination invariant in face recognition. The histogram equalization was applied to improve the performances of the AT (Affine Transform) algorithm. A novel illumination normalization method was introduced. Using the information of the distribution of the histogram,...
This paper investigates the score normalization technique for enhancing the performance of face authentication. We firstly discuss the thresholding approach for face authentication and put forward the “score variation” problem. Then, two possible solutions, Subject Specific Threshold (SST) and Score Normalization (SN), are discussed. But SST is obviously impractical to many face authentication applications...
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual information into AdaBoost, we propose an improved boosting algorithm in this paper. The proposed method fully examines the redundancy between candidate classifiers and selected classifiers. The classifiers thus selected are both...
In this paper, we propose an automatic method to set up a 3D morphable face model. The main idea is to combine the algorithm of Fast-AAM with Thin Plate Splines (TPS) for 3D data alignment. Our method is better than the algorithm of optical flow proposed in [3][5] because it avoids the local minima problem, and also it is better than the adaptive multi-resolution fitting algorithm [8][9] in 3D alignment...
We propose two new classifiers, one based on the classical Procrustes analysis and the other on the Moore-Penrose inverse in the context of face recognition. The Procrustes based classifier has recognition rates of 97.5%, 96.19%, 71.40% and 96.22% for the ORL, YALE, GIT and the FERET database respectively. The Moore-Penrose classifier has comparative recognition rates of 98%, 99.04%, 87.40% and 96...
Though authentication using biometric techniques has conveniences for people, security problems like the leakage of personal bio-information would be serious. Even if cancelable biometric is a good solution for the problems, only a few biometric authentication scheme with cancelable feature has been published. In this paper, we suggest a face authentication scheme with two security factors: password...
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