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Face recognition methods are evaluated against face image databases. Recent face image databases provide an evaluation protocol for an impartial comparison and assessment of where a facial recognition algorithm stands compared to other methods. Unfortunately, many authors test their facial recognition methods using either restricted face databases, random subsets from public databases, or do not follow...
The wide deployment of biometric recognition systems has raised several concerns regarding their security. Among other threats, morphing attacks consist of the infiltration of artificial images created using biometric information of two or more subjects. These morphed images are hence positively matched to several subjects. Recent studies have shown that such images pose a concrete threat to civil...
Light field cameras are emerging as powerful devices to capture rich scene representations that provide unique advantages for analysis and representation purposes. Some recent works have shown the power and usefulness of the richer information carried out by light field imaging, notably for face recognition. However, it is still difficult to fully assess how face recognition technology can benefit...
This paper presents a face recognition algorithm based on Local Binary Pattern (LBP) to be implemented in a Smartphone with Android operating system where the input image is obtained using the camera of such Smartphone. The LBP algorithm is used for Face characterization, due to its low complexity and its robustness light of this method is chosen to be applied in a Smartphone, this is because the...
Morphed face images are artificially generated images, which blend the facial images of two or more different data subjects into one. The resulting morphed image resembles the constituent faces, both in visual and feature representation. If a morphed image is enroled as a probe in a biometric system, the data subjects contributing to the morphed image will be verified against the enroled probe. As...
The high dimension and large computational complexity are shortcomings of feature extraction in multi-level histogram sequence local binary pattern (M-HSLBP). In order to overcome those problems, a face recognition algorithm based on the combination of multi-level histogram sequence center-symmetric local binary pattern (M-HCSLBP) and Fisherface is proposed in this paper. First, CS-LBP algorithm is...
In the calculation of rank minimization, the non-negative sparse low-rank representation classification (NSLRRC) regularizes nuclear norm's each singular value equally, but this limits its flexibility and ability to solve many practical problems, where the singular values with clear physical meanings ought to be treated differently. In this paper, a weighted non-negative sparse low-rank representation...
Face recognition is growingly becoming a very remarkable field in machine learning and artificial intelligence. In this paper, we introduce a modified scheme for face recognition based on the hybrid color model along with the Gabor Feature Extraction and Principal Component Analysis (PCA). Our algorithm is tested on two face databases namely, 'The MUCT Database' and 'The FEI Database' for recognition...
Recognition of Face in a group of people is a bit of difficult in now days, in this paper, a new method called Fuzzy Logic Local Ternary Pattern has been introduced. This FLTP method is a commanding technique to identify the faces clearly and even their emotions too. Here, several videos are taken in to the database and compares with query image. Using FLTP, recognizes the person is present in those...
In this paper, we present a new face recognition algorithm based on weighted deep face learning. Our proposed method composes of two steps: face detection and face feature extraction. The aim of face detection is to find an accurate face position. The face alignment is then applied by finding the facial landmarks in the face rectangle. With the help of face alignment the error rate of face recognition...
Face recognition is a fascinating research area which has potential applications in almost every field in this world. Having said this, there is a strong need for developing a stubborn system which can overcome all problems faced in recognizing a face correctly. The flow of face recognition system is preprocessing, Feature extraction and classification. Pre-processing includes image resizing, image...
Attendance automation has become one of the most important needs in educational institutions and work places across the world, since it saves time and accurate too. Face recognition system needs least human cooperation and is viable too. The system automatically detects the student's entry in the class and marks attendance for the particular student periodically. The data collected can be used by...
Compared to the traditional Gabor transform, the circularly symmetrical Gabor transform (CSGT) not only retains the characteristics of local and multi-resolution analysis, but also has the remarkable advantages of less redundancy and rotational invariance. Simultaneously, the collaborative representation-based classification with regularized least square (CRC-RLS) overcomes the shortcoming of the...
Face anti-spoofing is very significant to the security of face recognition. Many existing literatures focus on the study of photo attack. For the video attack, however, the related research efforts are still insufficient. In this paper, instead of extracting features from a single image, features are learned from video frames. To realize face anti-spoofing, the spatiotemporal features of continuous...
To predict criminal acts and to assure more security, the biometric remote recognition of people has lately been getting much interest among researchers. We propose in this paper to use biometric modalities that may be acquired remotely, which are the gait and the face. The gait is explored at 11 different angles of view with different styles of clothes using the CASIA Gait Datasets A and B. For the...
Feature refers to some relevant information which is present on images or faces. Feature extraction used to extract those features from the face. Among that bulk of keypoints, only robust features are detected by using feature descriptors. This paper analyzes 2 robust feature detector and descriptors are: Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF). These two robust...
We analyze the theoretical vulnerability of maximum a posteriori(MAP) speaker adaptation, which is widely used in practical speaker recognition systems. First, we proved that there exist a set of feature vectors, what are called wolves, which can impersonate almost all the registered speakers with probability asymptotically close to 1 with at most two trials. Second, our experiment shows that the...
This paper proposes a novel facial image representation Block-based Local Contrast Patterns (BLCP) for illumination-robust face recognition. This method is based on an effective texture descriptor local contrast patterns (LCP). We use the directed and undirected difference masks to calculate three types of local intensity contrasts: directed, undirected, and maximum difference responses. These response...
This paper studies the composition of portrait paintings and develops an algorithm to improve the composition of portrait photographs. The study of portrait paintings shows that placement of the face and the figure in portrait paintings is pose-related. Based on this observation, this paper develops an algorithm to improve the composition of a portrait photograph by learning the placement of the face...
This paper proposes a psychologically inspired convolutional neural network (PI-CNN) to achieve automatic facial beauty prediction. Different from the previous methods, the PI-CNN is a hierarchical model that facilitates both the facial beauty representation learning and predictor training. Inspired by the recent psychological studies, significant appearance features of facial detail, lighting and...
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