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Different pixel plays different roles in representing a face image. In this paper, we proposed a novel representation which integrates original and its virtual face image to represent test sample. This method first combines two adjacent columns of an original face image to generate corresponding virtual face image, and then classification algorithm is respectively applied to the original and virtual...
Illumination variation is a challenge of face recognition, especially in low light environments. In order to overcome the influence of low illumination image, this paper proposed a face recognition method of face image preprocessing before recognition, with illumination- reflection model of homomorphic filtering and image multiplication method of image preprocessing for getting the enhancement of...
The spatial pyramid feature learning methods, such as Spatial Pyramid Matching (SPM) and Sparse Coding based Spatial Pyramid Matching (ScSPM), have achieved significant performance in image categorization. While most of these methods are still based on manual-design features, such as SIFT, HOG and LBP, which limits the representation of data. In this paper, we propose a novel Sparse Autoencoder based...
This paper explores techniques for automatically recognizing the sentiment of facial expressions in social photos, especially those of politicians in the context of elections. We first use the Active Shape Model (ASM) to extract facial feature points. Next, the shape model points from the ASM are normalized to a standard shape and then submitted to a trained AdaBoost classifier to recognize the sentiment...
Identical twins pose a great challenge to face recognition due to high similarities in their appearances. Motivated by the psychological findings that facial motion contains identity signatures and the observation that twins may look alike but behave differently, we develop a talking profile to use the identity signatures in the facial motion to distinguish between identical twins. The talking profile...
As a powerful algorithm for face recognition, the proposed Two-Phase Test Sample Representation (TPTSR) increases the classification rate by dividing the recognition task into two steps. The first step intends to find the M most possible candidate training samples from the whole training set to match with the testing input, and the second phase classifies the testing sample to the class with the most...
In this paper, we propose a method for 3D facial expression recognition. The algorithm is composed of three steps. The first step is to extract the region of interested 3D face, some data preprocessing works, including face location, point cloud rotation and uniform distribution of points cloud, have been done in this step. Otherwise, the second step is feature extraction, novel features are extracted...
Face verification is defined as a person whose identity is claimed a priori will be compared with the person's individual template in database, and then the system checks whether the similarity between pattern and template is sufficient to provide access. In this paper we introduce a new procedure of face verification with an embedding Electoral College framework, which has been applied successfully...
There has been significant progress in improving the performance of computer-based face recognition algorithms over the last decade. Although algorithms have been tested and compared extensively with each other, there has been remarkably little work comparing the accuracy of computer-based human face recognition systems. We compared eight state-of-the-art face recognition algorithms with three different...
To reduce the dimensionality of the Gabor feature, this paper explores texture information from Gabor coefficients and presents two kinds of new Gabor texture representations for face recognition: Gabor real part-based texture representation (GRTR) and Gabor imaginary part-based texture representation (GITR). Specifically, GRTR and GITR are obtained using the generalized Gaussian distribution (GGD)...
An extension of local binary pattern, named Number Local binary pattern (NLBP), is presented for texture analysis. First, the method divides the patterns into uniform and non-uniform according to the uniform measure. Second, the non-uniform pattern is further divided into different groups based on the numbers of ‘1’ bits and ‘0’ bits. The experiment shows that NLBP achieves a good texture discrimination...
In recent years, single-mode face recognition has achieved great progress under the impetus of a variety of applications, and its recognition rate can reach as high as 99%. Heterogeneous face biometrics, namely face mapping between images captured in different spectral bands, has now become a hotspot. Our paper focuses on the problem of face recognition between registered visual (VIS) images and predicted...
Based on the face detection theory of Adaboost, incorporating with the program of Visual C++ in Windows, this paper designs a face detection system. This system realizes the function of face detection and increases detecting rate and speed by the combination of MIT face database and self-created face database, and the effective training of face database. Utilizing continuously adaptive mean shift...
One of the most challenging tasks for face recognition lies in the so-called one sample per person problem. Numerous face recognition techniques will suffer serious performance drop or even fail to work in this situation. To solving it, a method based on wavelet transform and virtual information (WV-based) is proposed in this paper. First, it performs the wavelet transform on face images, then it...
In this paper, we exploit the multi-modal face recognition capability by a comparative study on 6 fusion methods in the score level, which can be divided into 2 kinds: (1) simple fusion without data training, such as Sum, Product, Max and Min; (2) complex fusion including a predefined data training section, such as Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM). Our experiments...
This paper proposes a novel method using sparse representation to improve the performance of head pose estimation. Sparse Representation Classifier (SRC) has been applied in face recognition and the related problem. In this paper, we first argue that SRC is efficient in head pose estimation. Then we propose the Block based Spare Representation Classifier (BSRC) method to reduce the influence of the...
In this paper, we exploit the multi-modal face recognition capability by a comparative study on 8 fusion methods in the score level, including Sum, Product, Max, Min, Decision Template (DT), Dempster-Shafer Rule (DS), Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) methods. Our experiments are based on the CASIA 3D Face Database and can be divided into two modes: verification and...
In this paper, we evaluate the gender classification performance based on 3D faces according to three aspects: image resolution, data fusion and texture descriptor. Our experiments are based on CASIA 3D Face Database, which has 123 individuals in total including different expressions. Main conclusions are as follows: (1) Image resolution has little influence on the gender categorization performance,...
Facial expression extraction is the essential step of facial expression recognition. The paper presents a system that uses 28 facial feature key-points in images detection and Gabor wavelet filter provided with 5 frequencies, 8 orientations. In according to actual demand, It can extract the feature of low quality facial expression image target, and have good robust for automatic facial expression...
Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which employs a user dependent one way transformation based on a two stage hashing algorithm. We first hash the face image using a two stages robust image hashing technique,...
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