Relevant bibliographies by topics / Face verification

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Face verification'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 June 2025

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Journal articles on the topic "Face verification"

1

Zhang, Xue Zhi, Xiao Kang Tang, Qiong Zou, Yong Zhen Zhang, and Da Wei Zhang. "Video Based Face Verification." Applied Mechanics and Materials 556-562 (May 2014): 4893–96. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4893.

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A method of PCA face verification based fuzzy membership is proposed. Constructing the face gallery set through video streaming, using principal component analysis to feature extraction and designing a classifier based fuzzy membership. To verify face in accordance with the threshold principle of fuzzy pattern recognition. The method is compared to the method of PCA face verification, experimental results shows that the proposed method has higher accuracy and robustness.
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Chmielińska, Jolanta, and Jacek Jakubowski. "Biometrical driver face verification." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 19, no. 6 (2018): 68–72. http://dx.doi.org/10.24136/atest.2018.039.

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The paper discusses the problem of face verification in a driver monitoring system for the purpose of traffic safety. Two different methods of face verification were proposed. Both of them are based on a convolutional neural network and were developed with the use of a transfer learning technique. In the paper, the results produced by both proposed method have been presented and compared. Moreover, their advantages and disadvantages have been discussed.
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BEBIS, GEORGE, SATISHKUMAR UTHIRAM, and MICHAEL GEORGIOPOULOS. "FACE DETECTION AND VERIFICATION USING GENETIC SEARCH." International Journal on Artificial Intelligence Tools 09, no. 02 (2000): 225–46. http://dx.doi.org/10.1142/s0218213000000161.

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We consider the problem of searching for the face of a particular individual in a two-dimensional intensity image. This problem has many potential applications such as locating a person in a crowd using images obtained by surveillance cameras. There are two steps in solving this problem: first, face regions must be extracted from the image(s) (face detection) and second, candidate faces must be compared against a face of interest (face verification). Without any a-priori knowledge about the location and size of a face in an image, every possible image location and face size should be considered, leading to a very large search space. In this paper, we propose using Genetic Algorithms (GAs) for searching the image efficiently. Specifically, we use GAs to find image sub-windows that contain faces and in particular, the face of interest. Each sub-window is evaluated using a fitness function containing two terms: the first term favors sub-windows containing faces while the second term favors sub-windows containing faces similar to the face of interest. Both terms have been derived using the theory of eigenspaces. A set of increasingly complex scenes demonstrate the performance of the proposed genetic-search approach.
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Grudzień, Artur, Marcin Kowalski, and Norbert Pałka. "Thermal Face Verification through Identification." Sensors 21, no. 9 (2021): 3301. http://dx.doi.org/10.3390/s21093301.

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This paper reports on a new approach to face verification in long-wavelength infrared radiation. Two face images were combined into one double image, which was then used as an input for a classification based on neural networks. For testing, we exploited two external and one homemade thermal face databases acquired in various variants. The method is reported to achieve a true acceptance rate of about 83%. We proved that the proposed method outperforms other studied baseline methods by about 20 percentage points. We also analyzed the issue of extending the performance of algorithms. We believe that the proposed double image method can also be applied to other spectral ranges and modalities different than the face.
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Manda, Bappaditya, Xudong Jiang, and Alex Kot. "Face Verification Using Modeled Eigenspectrum." Open Artificial Intelligence Journal 2, no. 1 (2008): 35–45. http://dx.doi.org/10.2174/1874061800802010035.

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Face verification is different from face identification task. Some traditional subspace methods that work well in face identification may suffer from severe over-fitting problem when applied for the verification task. Conventional discriminative methods such as linear discriminant analysis (LDA) and its variants are highly sensitive to the training data, which hinders them from achieving high verification accuracy. This work proposes an eigenspectrum model that alleviates the over-fitting problems by replacing the unreliable small and zero eigenvalues with the model values. It also enables the discriminant evaluation in the whole space to extract the low dimensional features effectively. The proposed approach is evaluated and compared with 8 popular subspace based methods for a face verification task. Experimental results on three face databases show that the proposed method consistently outperforms others.
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Sao, Anil Kumar, and B. Yegnanarayana. "Face Verification Using Template Matching." IEEE Transactions on Information Forensics and Security 2, no. 3 (2007): 636–41. http://dx.doi.org/10.1109/tifs.2007.902920.

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Troncoso-Pastoriza, J. R., D. Gonzalez-Jimenez, and F. Perez-Gonzalez. "Fully Private Noninteractive Face Verification." IEEE Transactions on Information Forensics and Security 8, no. 7 (2013): 1101–14. http://dx.doi.org/10.1109/tifs.2013.2262273.

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Matas, J., K. Jonsson, and J. Kittler. "Fast face localisation and verification." Image and Vision Computing 17, no. 8 (1999): 575–81. http://dx.doi.org/10.1016/s0262-8856(98)00176-0.

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Jang, Jun-Su, Kuk-Hyun Han, and Jong-Hwan Kim. "Evolutionary algorithm-based face verification." Pattern Recognition Letters 25, no. 16 (2004): 1857–65. http://dx.doi.org/10.1016/j.patrec.2004.08.013.

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Dhomne, Amit, and Pankaj Kumar Sa. "Face Verification Using Deep Learning." JIMS8I � International Journal of Information Communication and Computing Technology 6, no. 1 (2018): 332. http://dx.doi.org/10.5958/2347-7202.2018.00003.8.

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Dissertations / Theses on the topic "Face verification"

1

Romano, Raquel Andrea. "Real-time face verification." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36649.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.<br>Includes bibliographical references (p. 57-59).<br>by Raquel Andrea Romano.<br>M.S.
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Short, J. "Illumination invariance for face verification." Thesis, University of Surrey, 2006. http://epubs.surrey.ac.uk/843404/.

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The task of face verification is made more difficult when the illumination conditions of image capture are not constrained. The differences in illumination conditions between the stored images of the client and the probe image can be lessened by the application of photometric normalisation. Photometric normalisation is the method of pre-processing an image to a representation that is robust to the illumination conditions of image capture. This thesis presents experiments comparing several photometric normalisation methods. The results demonstrate that the anisotropic smoothing pre-processing algorithm of Gross and Brajovic yields the best results of the photometric normalisations tested. The thesis presents an investigation into the behaviour of the anisotropic smoothing method, showing that performance is sensitive to the selection of its parameter. A method of optimising this parameter is suggested and experimental results show that it offers an improvement in verification rates. The variation of illumination across regions of the face is smaller than across the whole face. A novel component-based approach to face verification is presented to take advantage of this fact. The approach consists of carrying out verification on a number of images containing components of the face and fusing the result. As the component images are more robust to illumination, the choice of photometric normalisation is again investigated in the component-based context. The thesis presents the useful result that the simpler normalisations offer the best results when applied to facial component images. Experiments investigating the various methods of fusing the information from the components are presented, as is the issue of score normalisation. Methods of selecting which components are most useful for verification are also tested. The method of pruning the negative components of the linear discriminant analysis weight vector has been applied to the task of selecting the best subset of face components for verification. The pruned linear discriminant analysis method does not perform as well as the well known sequential floating forward selection method on the well illuminated XM2VTS database, however it achieves better generalisation when applied to the more challenging conditions of the XM2VTS dark set.
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McCool, Christopher Steven. "Hybrid 2D and 3D face verification." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16436/1/Christopher_McCool_Thesis.pdf.

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Face verification is a challenging pattern recognition problem. The face is a biometric that, we as humans, know can be recognised. However, the face is highly deformable and its appearance alters significantly when the pose, illumination or expression changes. These changes in appearance are most notable for texture images, or two-dimensional (2D) data. But the underlying structure of the face, or three dimensional (3D) data, is not changed by pose or illumination variations. Over the past five years methods have been investigated to combine 2D and 3D face data to improve the accuracy and robustness of face verification. Much of this research has examined the fusion of a 2D verification system and a 3D verification system, known as multi-modal classifier score fusion. These verification systems usually compare two feature vectors (two image representations), a and b, using distance or angular-based similarity measures. However, this does not provide the most complete description of the features being compared as the distances describe at best the covariance of the data, or the second order statistics (for instance Mahalanobis based measures). A more complete description would be obtained by describing the distribution of the feature vectors. However, feature distribution modelling is rarely applied to face verification because a large number of observations is required to train the models. This amount of data is usually unavailable and so this research examines two methods for overcoming this data limitation: 1. the use of holistic difference vectors of the face, and 2. by dividing the 3D face into Free-Parts. The permutations of the holistic difference vectors is formed so that more observations are obtained from a set of holistic features. On the other hand, by dividing the face into parts and considering each part separately many observations are obtained from each face image; this approach is referred to as the Free-Parts approach. The extra observations from both these techniques are used to perform holistic feature distribution modelling and Free-Parts feature distribution modelling respectively. It is shown that the feature distribution modelling of these features leads to an improved 3D face verification system and an effective 2D face verification system. Using these two feature distribution techniques classifier score fusion is then examined. This thesis also examines methods for performing classifier fusion score fusion. Classifier score fusion attempts to combine complementary information from multiple classifiers. This complementary information can be obtained in two ways: by using different algorithms (multi-algorithm fusion) to represent the same face data for instance the 2D face data or by capturing the face data with different sensors (multimodal fusion) for instance capturing 2D and 3D face data. Multi-algorithm fusion is approached as combining verification systems that use holistic features and local features (Free-Parts) and multi-modal fusion examines the combination of 2D and 3D face data using all of the investigated techniques. The results of the fusion experiments show that multi-modal fusion leads to a consistent improvement in performance. This is attributed to the fact that the data being fused is collected by two different sensors, a camera and a laser scanner. In deriving the multi-algorithm and multi-modal algorithms a consistent framework for fusion was developed. The consistent fusion framework, developed from the multi-algorithm and multimodal experiments, is used to combine multiple algorithms across multiple modalities. This fusion method, referred to as hybrid fusion, is shown to provide improved performance over either fusion system on its own. The experiments show that the final hybrid face verification system reduces the False Rejection Rate from 8:59% for the best 2D verification system and 4:48% for the best 3D verification system to 0:59% for the hybrid verification system; at a False Acceptance Rate of 0:1%.
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McCool, Christopher Steven. "Hybrid 2D and 3D face verification." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16436/.

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Face verification is a challenging pattern recognition problem. The face is a biometric that, we as humans, know can be recognised. However, the face is highly deformable and its appearance alters significantly when the pose, illumination or expression changes. These changes in appearance are most notable for texture images, or two-dimensional (2D) data. But the underlying structure of the face, or three dimensional (3D) data, is not changed by pose or illumination variations. Over the past five years methods have been investigated to combine 2D and 3D face data to improve the accuracy and robustness of face verification. Much of this research has examined the fusion of a 2D verification system and a 3D verification system, known as multi-modal classifier score fusion. These verification systems usually compare two feature vectors (two image representations), a and b, using distance or angular-based similarity measures. However, this does not provide the most complete description of the features being compared as the distances describe at best the covariance of the data, or the second order statistics (for instance Mahalanobis based measures). A more complete description would be obtained by describing the distribution of the feature vectors. However, feature distribution modelling is rarely applied to face verification because a large number of observations is required to train the models. This amount of data is usually unavailable and so this research examines two methods for overcoming this data limitation: 1. the use of holistic difference vectors of the face, and 2. by dividing the 3D face into Free-Parts. The permutations of the holistic difference vectors is formed so that more observations are obtained from a set of holistic features. On the other hand, by dividing the face into parts and considering each part separately many observations are obtained from each face image; this approach is referred to as the Free-Parts approach. The extra observations from both these techniques are used to perform holistic feature distribution modelling and Free-Parts feature distribution modelling respectively. It is shown that the feature distribution modelling of these features leads to an improved 3D face verification system and an effective 2D face verification system. Using these two feature distribution techniques classifier score fusion is then examined. This thesis also examines methods for performing classifier fusion score fusion. Classifier score fusion attempts to combine complementary information from multiple classifiers. This complementary information can be obtained in two ways: by using different algorithms (multi-algorithm fusion) to represent the same face data for instance the 2D face data or by capturing the face data with different sensors (multimodal fusion) for instance capturing 2D and 3D face data. Multi-algorithm fusion is approached as combining verification systems that use holistic features and local features (Free-Parts) and multi-modal fusion examines the combination of 2D and 3D face data using all of the investigated techniques. The results of the fusion experiments show that multi-modal fusion leads to a consistent improvement in performance. This is attributed to the fact that the data being fused is collected by two different sensors, a camera and a laser scanner. In deriving the multi-algorithm and multi-modal algorithms a consistent framework for fusion was developed. The consistent fusion framework, developed from the multi-algorithm and multimodal experiments, is used to combine multiple algorithms across multiple modalities. This fusion method, referred to as hybrid fusion, is shown to provide improved performance over either fusion system on its own. The experiments show that the final hybrid face verification system reduces the False Rejection Rate from 8:59% for the best 2D verification system and 4:48% for the best 3D verification system to 0:59% for the hybrid verification system; at a False Acceptance Rate of 0:1%.
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Bourlai, Thirimachos. "Designing a smart card face verification system." Thesis, University of Surrey, 2006. http://epubs.surrey.ac.uk/843504/.

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This thesis describes a face verification system that is smart-card-based. The objectives were to identify the key parameters that affect the design of such a system, to investigate die general optimisation problem and test its robustness when each key parameter is optimised. Some of these parameters have been coarsely investigated in the literature in the context of the general face recognition problem. However, the previous work only partially fulfilled the requirements of a smart-card-based system, in which the severe engineering constraints and limitations imposed by smart cards have to be taken into account in the overall design process. To address these problems on the proposed fully localised architecture of the smart card face verification system (SCFVS), the work starts with the selection of the client specific linear discriminant analysis (CS-LDA) algorithm, suitable to be ported to the target platform on which the biometric process can run. Then the main functional parts of the system are presented: face image geometric alignment, photometric normalisation, feature extraction, and on-card verification. Each part consists of a series of basic steps, where the role of each step is fixed. However, the algorithm is systematically varied in some steps to investigate the effect on system performance, and system complexity in terms of speed and memory management. Two major problems have been considered. The first problem are the restrictions that both face verification and smart card technology impose and the second is the extreme complexity of the system, in terms of the number of processing stages and system design parameters. In the simplified search procedure adopted, a number of parameters has been selected out of the complete parameter set involved in a generic SCFVS. This set was recommended by previous main-frame based studies, and deemed to provide acceptable performance. System optimisation in the context of smart card implementation has been conducted starting from those parameters involved in the pre-processing stage of the system, and then those involved in the remaining stages. A joint optimisation framework of the key parameters can also be adopted, assuming that then- effect is independent. Experimental results obtained on a number of publicly available face databases (used to evaluate the system performance) show the significant benefits of this design both in terms of performance and system speed. The different results achieved on different databases indicate that optimum parameters of the system are, to a certain extent, training database dependent.
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Sanderson, Conrad, and conradsand@ieee org. "Automatic Person Verification Using Speech and Face Information." Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030422.105519.

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Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be compromised. Thus new verification methods have emerged, where the password has either been replaced by, or used in addition to, biometrics such as the person’s speech, face image or fingerprints. Apart from the ATM example described above, biometrics can be applied to other areas, such as telephone & internet based banking, airline reservations & check-in, as well as forensic work and law enforcement applications. Biometric systems based on face images and/or speech signals have been shown to be quite effective. However, their performance easily degrades in the presence of a mismatch between training and testing conditions. For speech based systems this is usually in the form of channel distortion and/or ambient noise; for face based systems it can be in the form of a change in the illumination direction. A system which uses more than one biometric at the same time is known as a multi-modal verification system; it is often comprised of several modality experts and a decision stage. Since a multi-modal system uses complimentary discriminative information, lower error rates can be achieved; moreover, such a system can also be more robust, since the contribution of the modality affected by environmental conditions can be decreased. This thesis makes several contributions aimed at increasing the robustness of single- and multi-modal verification systems. Some of the major contributions are listed below. The robustness of a speech based system to ambient noise is increased by using Maximum Auto-Correlation Value (MACV) features, which utilize information from the source part of the speech signal. A new facial feature extraction technique is proposed (termed DCT-mod2), which utilizes polynomial coefficients derived from 2D Discrete Cosine Transform (DCT) coefficients of spatially neighbouring blocks. The DCT-mod2 features are shown to be robust to an illumination direction change as well as being over 80 times quicker to compute than 2D Gabor wavelet derived features. The fragility of Principal Component Analysis (PCA) derived features to an illumination direction change is solved by introducing a pre-processing step utilizing the DCT-mod2 feature extraction. We show that the enhanced PCA technique retains all the positive aspects of traditional PCA (that is, robustness to compression artefacts and white Gaussian noise) while also being robust to the illumination direction change. Several new methods, for use in fusion of speech and face information under noisy conditions, are proposed; these include a weight adjustment procedure, which explicitly measures the quality of the speech signal, and a decision stage comprised of a structurally noise resistant piece-wise linear classifier, which attempts to minimize the effects of noisy conditions via structural constraints on the decision boundary.
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Sanderson, Conrad. "Automatic Person Verification Using Speech and Face Information." Thesis, Griffith University, 2003. http://hdl.handle.net/10072/367191.

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Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be compromised. Thus new verification methods have emerged, where the password has either been replaced by, or used in addition to, biometrics such as the person’s speech, face image or fingerprints. Apart from the ATM example described above, biometrics can be applied to other areas, such as telephone & internet based banking, airline reservations & check-in, as well as forensic work and law enforcement applications. Biometric systems based on face images and/or speech signals have been shown to be quite effective. However, their performance easily degrades in the presence of a mismatch between training and testing conditions. For speech based systems this is usually in the form of channel distortion and/or ambient noise; for face based systems it can be in the form of a change in the illumination direction. A system which uses more than one biometric at the same time is known as a multi-modal verification system; it is often comprised of several modality experts and a decision stage. Since a multi-modal system uses complimentary discriminative information, lower error rates can be achieved; moreover, such a system can also be more robust, since the contribution of the modality affected by environmental conditions can be decreased. This thesis makes several contributions aimed at increasing the robustness of single- and multi-modal verification systems. Some of the major contributions are listed below. The robustness of a speech based system to ambient noise is increased by using Maximum Auto-Correlation Value (MACV) features, which utilize information from the source part of the speech signal. A new facial feature extraction technique is proposed (termed DCT-mod2), which utilizes polynomial coefficients derived from 2D Discrete Cosine Transform (DCT) coefficients of spatially neighbouring blocks. The DCT-mod2 features are shown to be robust to an illumination direction change as well as being over 80 times quicker to compute than 2D Gabor wavelet derived features. The fragility of Principal Component Analysis (PCA) derived features to an illumination direction change is solved by introducing a pre-processing step utilizing the DCT-mod2 feature extraction. We show that the enhanced PCA technique retains all the positive aspects of traditional PCA (that is, robustness to compression artefacts and white Gaussian noise) while also being robust to the illumination direction change. Several new methods, for use in fusion of speech and face information under noisy conditions, are proposed; these include a weight adjustment procedure, which explicitly measures the quality of the speech signal, and a decision stage comprised of a structurally noise resistant piece-wise linear classifier, which attempts to minimize the effects of noisy conditions via structural constraints on the decision boundary.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Microelectronic Engineering<br>Full Text
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Jonsson, K. T. "Robust correlation and support vector machines for face identification." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/799/.

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Ramos, Sanchez M. Ulises. "Aspects of facial biometrics for verification of personal identity." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/792194/.

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Tan, Teewoon. "HUMAN FACE RECOGNITION BASED ON FRACTAL IMAGE CODING." University of Sydney. Electrical and Information Engineering, 2004. http://hdl.handle.net/2123/586.

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Human face recognition is an important area in the field of biometrics. It has been an active area of research for several decades, but still remains a challenging problem because of the complexity of the human face. In this thesis we describe fully automatic solutions that can locate faces and then perform identification and verification. We present a solution for face localisation using eye locations. We derive an efficient representation for the decision hyperplane of linear and nonlinear Support Vector Machines (SVMs). For this we introduce the novel concept of $\rho$ and $\eta$ prototypes. The standard formulation for the decision hyperplane is reformulated and expressed in terms of the two prototypes. Different kernels are treated separately to achieve further classification efficiency and to facilitate its adaptation to operate with the fast Fourier transform to achieve fast eye detection. Using the eye locations, we extract and normalise the face for size and in-plane rotations. Our method produces a more efficient representation of the SVM decision hyperplane than the well-known reduced set methods. As a result, our eye detection subsystem is faster and more accurate. The use of fractals and fractal image coding for object recognition has been proposed and used by others. Fractal codes have been used as features for recognition, but we need to take into account the distance between codes, and to ensure the continuity of the parameters of the code. We use a method based on fractal image coding for recognition, which we call the Fractal Neighbour Distance (FND). The FND relies on the Euclidean metric and the uniqueness of the attractor of a fractal code. An advantage of using the FND over fractal codes as features is that we do not have to worry about the uniqueness of, and distance between, codes. We only require the uniqueness of the attractor, which is already an implied property of a properly generated fractal code. Similar methods to the FND have been proposed by others, but what distinguishes our work from the rest is that we investigate the FND in greater detail and use our findings to improve the recognition rate. Our investigations reveal that the FND has some inherent invariance to translation, scale, rotation and changes to illumination. These invariances are image dependent and are affected by fractal encoding parameters. The parameters that have the greatest effect on recognition accuracy are the contrast scaling factor, luminance shift factor and the type of range block partitioning. The contrast scaling factor affect the convergence and eventual convergence rate of a fractal decoding process. We propose a novel method of controlling the convergence rate by altering the contrast scaling factor in a controlled manner, which has not been possible before. This helped us improve the recognition rate because under certain conditions better results are achievable from using a slower rate of convergence. We also investigate the effects of varying the luminance shift factor, and examine three different types of range block partitioning schemes. They are Quad-tree, HV and uniform partitioning. We performed experiments using various face datasets, and the results show that our method indeed performs better than many accepted methods such as eigenfaces. The experiments also show that the FND based classifier increases the separation between classes. The standard FND is further improved by incorporating the use of localised weights. A local search algorithm is introduced to find a best matching local feature using this locally weighted FND. The scores from a set of these locally weighted FND operations are then combined to obtain a global score, which is used as a measure of the similarity between two face images. Each local FND operation possesses the distortion invariant properties described above. Combined with the search procedure, the method has the potential to be invariant to a larger class of non-linear distortions. We also present a set of locally weighted FNDs that concentrate around the upper part of the face encompassing the eyes and nose. This design was motivated by the fact that the region around the eyes has more information for discrimination. Better performance is achieved by using different sets of weights for identification and verification. For facial verification, performance is further improved by using normalised scores and client specific thresholding. In this case, our results are competitive with current state-of-the-art methods, and in some cases outperform all those to which they were compared. For facial identification, under some conditions the weighted FND performs better than the standard FND. However, the weighted FND still has its short comings when some datasets are used, where its performance is not much better than the standard FND. To alleviate this problem we introduce a voting scheme that operates with normalised versions of the weighted FND. Although there are no improvements at lower matching ranks using this method, there are significant improvements for larger matching ranks. Our methods offer advantages over some well-accepted approaches such as eigenfaces, neural networks and those that use statistical learning theory. Some of the advantages are: new faces can be enrolled without re-training involving the whole database; faces can be removed from the database without the need for re-training; there are inherent invariances to face distortions; it is relatively simple to implement; and it is not model-based so there are no model parameters that need to be tweaked.
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Books on the topic "Face verification"

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Jonathon, Phillips P., Moon Hyeonjoon, and National Institute of Standards and Technology (U.S.), eds. The FERET verification testing protocol for face recognition algorithms. U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1998.

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Mezaris, Vasileios, Lyndon Nixon, Symeon Papadopoulos, and Denis Teyssou, eds. Video Verification in the Fake News Era. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26752-0.

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Office, General Accounting. Welfare eligibility: Deficit Reduction Act income verification issues : fact sheet for the ranking minority member, Subcommittee on Oversight of Government Management, Committee on Governmental Affairs, United States Senate. The Office, 1987.

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Office, General Accounting. Welfare eligibility: Deficit Reduction Act income verification issues : fact sheet for the ranking minority member, Subcommittee on Oversight of Government Management, Committee on Governmental Affairs, United States Senate. The Office, 1987.

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Office, General Accounting. Welfare eligibility: Deficit Reduction Act income verification issues : fact sheet for the ranking minority member, Subcommittee on Oversight of Government Management, Committee on Governmental Affairs, United States Senate. The Office, 1987.

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Lu, Jiwen, and Haibin Yan. Facial Kinship Verification: A Machine Learning Approach. Springer, 2017.

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Ángel Serrano Sánchez de León. Face Recognition and Verification with Gabor Filters. Editorial Dykinson, S.L., 2012.

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Ángel Serrano Sánchez de León. Face Recognition and Verification with Gabor Filters. Editorial Dykinson, S.L., 2012.

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Ángel Serrano Sánchez de León. Face Recognition and Verification with Gabor Filters. Editorial Dykinson, S.L., 2012.

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Ángel Serrano Sánchez de León. Face Recognition and Verification with Gabor Filters. Editorial Dykinson, S.L., 2012.

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Book chapters on the topic "Face verification"

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Lin, Liang, Dongyu Zhang, Ping Luo, and Wangmeng Zuo. "Face Verification." In Human Centric Visual Analysis with Deep Learning. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2387-4_9.

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Bredin, Hervé, Aurélien Mayoue, and Gérard Chollet. "Talking-face Verification." In Guide to Biometric Reference Systems and Performance Evaluation. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-292-0_10.

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Zhang, David, and Guangming Lu. "3D Face Verification System." In 3D Biometrics. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7400-5_14.

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Mohd Zainal, Mohd Ridzuwary, Hafizah Husain, Salina Abdul Samad, and Aini Hussain. "Face Verification Using Multiple Localized Face Features." In Advances in Visual Informatics. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02958-0_9.

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Short, James, Josef Kittler, and Kieron Messer. "Photometric Normalisation for Face Verification." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11527923_64.

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Kittler, J., Y. P. Li, J. Matas, and M. U. Ramos Sánchez. "Lip-shape dependent face verification." In Audio- and Video-based Biometric Person Authentication. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0015980.

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Salimi, Fahimeh, Mohammad T. Sadeghi, Mohammad S. Moin, and Josef Kittler. "Face Verification Using Colour Kernels." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02611-9_52.

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Christiansen, Eric, Iljung S. Kwak, Serge Belongie, and David Kriegman. "Face Box Shape and Verification." In Advances in Visual Computing. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41914-0_54.

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Smiatacz, Maciej. "Subspace Algorithms for Face Verification." In Computer Recognition Systems 4. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20320-6_3.

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Lu, Xiaojun, Yang Wang, Weilin Zhang, Song Ding, and Wuming Jiang. "Deep CNNs for Face Verification." In Biometric Recognition. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46654-5_10.

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Conference papers on the topic "Face verification"

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Bai, Ruwen, Lin Shi, Shuo Liu, and Jie Chen. "Research on Standard Verification Reference Model for Fake Face Forensics." In 2024 9th International Conference on Signal and Image Processing (ICSIP). IEEE, 2024. http://dx.doi.org/10.1109/icsip61881.2024.10671461.

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Fournier-Montgieux, Alexandre, Michaël Soumm, Adrian Popescu, Bertrand Luvison, and Hervé Le Borgne. "Fairer Analysis and Demographically Balanced Face Generation for Fairer Face Verification." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00276.

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Hashmi, Huma, Hamza Ahmed, Rana Ali Ahmar, Muhammad Ibrahim Syed, Khurram Khan, and Zahid Mahmood. "Towards Electronic Voting Using Face Verification Technology." In 2024 19th International Conference on Emerging Technologies (ICET). IEEE, 2024. https://doi.org/10.1109/icet63392.2024.10935228.

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Lin, Chen, Zhouyingcheng Liao, Peng Zhou, Jianguo Hu, and Bingbing Ni. "Live Face Verification with Multiple Instantialized Local Homographic Parameterization." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/113.

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State-of-the-art live face verification methods would easily be attacked by recorded facial expression sequence. This work directly addresses this issue via proposing a patch-wise motion parameterization based verification network infrastructure. This method directly explores the underlying subtle motion difference between the facial movements re-captured from a planer screen (e.g., a pad) and those from a real face; therefore interactive facial expression is no longer required. Furthermore, inspired by the fact that ?a fake facial movement sequence MUST contains many patch-wise fake sequences?, we embed our network into a multiple instance learning framework, which further enhance the recall rate of the proposed technique. Extensive experimental results on several face benchmarks well demonstrate the superior performance of our method.
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Du, Liang, and Haibin Ling. "Cross-age face verification by coordinating with cross-face age verification." In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2015. http://dx.doi.org/10.1109/cvpr.2015.7298846.

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Khanna, Alankrit, Anisha Thakur, Aprajita Tewari, and Aruna Bhat. "CROSS-AGE FACE VERIFICATION USING FACE AGING." In IPMV 2020: 2020 2nd International Conference on Image Processing and Machine Vision. ACM, 2020. http://dx.doi.org/10.1145/3421558.3421573.

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Kittler, J., R. Ghaderi, T. Windeatt, and J. Matas. "Face Verification via ECOC." In British Machine Vision Conference 2001. British Machine Vision Association, 2001. http://dx.doi.org/10.5244/c.15.61.

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Hu, Junlin, Yongxin Ge, Jiwen Lu, and Xin Feng. "Makeup-robust face verification." In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638073.

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Hong, Wei, Haizhou Ai, Li Zhuang, and Guang-you Xu. "Video-based face verification." In Multispectral Image Processing and Pattern Recognition, edited by Tianxu Zhang, Bir Bhanu, and Ning Shu. SPIE, 2001. http://dx.doi.org/10.1117/12.441443.

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Costa, Filipe, Marcos Vinícius L. Melo, Igor Gadelha, Guilherme Fôlego, Larissa Gambaro, and André Rodrigues. "Self-portrait to ID Document face matching: CNN-Based face verification in cross-domain scenario." In Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/wvc.2021.18885.

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Face verification approaches determine whether two given faces are from the same person. Recently, a new demand for face verification application which has become popular in commercial applications is the self-portrait and ID face matching, in which we compare the faces of a selfie shot by a subject and the face in a picture of her identification document. In this work, we proposed a novel approach for face verification in a cross-domain scenario, assuming we have only two images for each subject in the dataset. The method is based on siamese architecture with triplet-loss function. Experiments show the proposed model reaches good effectiveness for cross-domain face verification with low error rates, in comparison to other works of the literature.
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Reports on the topic "Face verification"

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Hanaoka, Kayee. Face Analysis Technology Evaluation: Age Estimation and Verification. National Institute of Standards and Technology, 2024. http://dx.doi.org/10.6028/nist.ir.8525.

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Rizvi, Syed A., P. Jonathon Phillips, and Hyeonjoon Moon. The FERET verification testing protocol for face recognition algorithms. National Institute of Standards and Technology, 1998. http://dx.doi.org/10.6028/nist.ir.6281.

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Azcárate Ortega, Almudena, Laetitia Cesari, and James Revill. Space Dossier 8 – Constant Vigilance? Verification and Monitoring for Space Security. UNIDIR, 2023. http://dx.doi.org/10.37559/wmd/23/space/04.

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In the face of space's ever-increasing importance to humankind, the ongoing development of counterspace capabilities by several States creates new forms of threats to space assets and infrastructure. As such, policy options to reduce or prevent the weaponization of space through arms control, disarmament and wider governance are increasingly important to ensure the security and sustainability of space operations. To inform policymaking in this area, it is useful to understand the options available for monitoring and verification in space. To explore the potential for verification for space security further, this report examines some of the tools and technologies of relevance to verification in space and how these tools could be applied to verify and monitor present and future frameworks related to space security.
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Ahmed, Hasnat, and Wahid bin Ahsan. Improving the Quality and Credibility of Educational Content on Social Media Platforms in Bangladesh. Userhub, 2024. http://dx.doi.org/10.58947/journal.xtcq54.

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This study investigates the quality and credibility of educational content on social media platforms learners in Bangladesh use. Using a mixed-methods approach, 80 survey responses and 30 in-depth interviews were analyzed to assess how learners engage with educational content, the challenges they face in verifying authenticity, and potential solutions. Findings show that Facebook is the primary platform for educational purposes, but users struggle with misinformation, weak content verification, and distracting advertisements. Although 63% of participants cross-referenced information, many infrequently verified content, exposing them to unreliable materials. Participants recommended implementing stronger fact-checking mechanisms, promoting digital literacy, and incentivizing the creation of high-quality content. This study contributes to ongoing discussions about enhancing content credibility on digital platforms and emphasizes the need for robust verification tools to support learners in developing countries like Bangladesh.
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Findlay, Trevor. The Role of International Organizations in WMD Compliance and Enforcement: Autonomy, Agency, and Influence. The United Nations Institute for Disarmament Research, 2020. http://dx.doi.org/10.37559/wmd/20/wmdce9.

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Major multilateral arms control and disarmament treaties dealing with weapons of mass destruction (WMD) often have mandated an international organization to monitor and verify State party compliance and to handle cases of non-compliance. There are marked differences in the mandates and technical capabilities of these bodies. Nonetheless, they often face the same operational and existential challenges. This report looks at the role of multilateral verification bodies, especially their secretariats, in dealing with compliance and enforcement, the extent to which they achieve “agency” and “influence” in doing so, and whether and how such capacities might be enhanced. In WMD organizations it is the governing bodies that make decisions about noncompliance and enforcement. The role of their secretariats is to manage the monitoring and verification systems, analyse the resulting data – and data from other permitted sources – and alert their governing bodies to suspicions of non-compliance. Secretariats are expected to be impartial, technically oriented and professional. It is when a serious allegation of non-compliance arises that their role becomes most sensitive politically and most vital. The credibility of Secretariats in these instances will depend on the agency and influence that they have accumulated. There are numerous ways in which an international secretariat can position itself for maximum agency and influence, essentially by making itself indispensable to member States and the broader international community. It can achieve this by engaging with multiple stakeholders, aiming for excellence in its human and technical resources, providing timely and sustainable implementation assistance, ensuring an appropriate organizational culture and, perhaps most of all, understanding that knowledge is power. The challenge for supporters of international verification organizations is to enhance those elements that give them agency and influence and minimize those that lead to inefficiencies, dysfunction and, most damaging of all, political interference in verification and compliance judgements.
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Smirnov, Serhii. Медіастандарти та фактчекінг в контексті психологічних бар’єрів, глибинних переконань та традицій. Ivan Franko National University of Lviv, 2023. http://dx.doi.org/10.30970/vjo.2023.52-53.11726.

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Denial by the Russians of the established facts of genocide and looting by their military in the Ukrainian cities and villages occupied by them and the belief in their version of some people and groups made the main objective of the study to find out to what extent media standards and information verification mechanisms work in conditions of deep convictions and the presence of psychological barriers. For this purpose, a task was chosen based on a politically neutral example that is understandable to the general public – the (non)existence of Santa Claus; verify its submission to the media with strict standards; find publications on this topic on fact-checking platforms; check the effectiveness of fact-checking tools. The methodological basis of the research was content and frame analysis of publications and news, factual, philological, semantic analyzes and an experiment – verification of publications using fact-checking tools. The result of the study was that deeply held beliefs, public opinion and pressure, and psychological barriers constitute a serious problem. It becomes difficult to publicize and promulgate the truth about the narrative supported by a large number of supporters with their statements, explanations and even events created for this. Even such media as AP or the fact-checking platform Politifact in such conditions deviate from the standards adopted for themselves. And even what started as a holiday joke – tracking Santa’s flight with NORAD radars – fact-checking tools will confirm that the radars are indeed tracking Russian planes and Santa Claus’ sleigh. The significance of the results is that the audience of the deliberate deception, which has accepted it as true, will defend it even in the face of irrefutable evidence. This is, in fact, the case with the genocide in Bucha and other cities of Ukraine, where Russians are trying to dispute the confirmed killings of civilians and looting by the Russian military. At the same time, taking this into account, it can also be assumed that a test that leads to a paradoxical conclusion (we know one thing but claim another) can become a tool for revealing the irrational deep beliefs of certain groups or societies and their causes or weaknesses. Key-words: social media, facts, fact check, media standards, fakes.
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Leff, Jonah, and Einas Mohammed. An Innovative Approach to United Nations Arms Embargoes. UNIDIR, 2020. http://dx.doi.org/10.37559/caap/20/wam/06.

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The Joint Verification Team on weapons and ammunition in Somalia represents an innovative approach to monitoring and verifying the implementation of Security Council arms embargoes. This observation paper sets out the establishment, methodology, role and activities of the Joint Verification Team, while cataloguing the challenges faced. The paper provides a series of key reflections on weapons and ammunition management in Somalia and considers how the Joint Verification Team might be replicated in other contexts
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Palomo, B., and J. Sedano. WhatsApp as a verification tool for fake news. The case of B de Bulo. Revista Latina de Comunicación Social, 2018. http://dx.doi.org/10.4185/rlcs-2018-1312en.

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Baader, Franz, and Marcel Lippmann. Runtime Verification Using a Temporal Description Logic Revisited. Technische Universität Dresden, 2014. http://dx.doi.org/10.25368/2022.203.

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Formulae of linear temporal logic (LTL) can be used to specify (wanted or unwanted) properties of a dynamical system. In model checking, the system’s behaviour is described by a transition system, and one needs to check whether all possible traces of this transition system satisfy the formula. In runtime verification, one observes the actual system behaviour, which at any point in time yields a finite prefix of a trace. The task is then to check whether all continuations of this prefix to a trace satisfy (violate) the formula. More precisely, one wants to construct a monitor, i.e., a finite automaton that receives the finite prefix as input and then gives the right answer based on the state currently reached. In this paper, we extend the known approaches to LTL runtime verification in two directions. First, instead of propositional LTL we use the more expressive temporal logic ALC-LTL, which can use axioms of the Description Logic (DL) ALC instead of propositional variables to describe properties of single states of the system. Second, instead of assuming that the observed system behaviour provides us with complete information about the states of the system, we assume that states are described in an incomplete way by ALC-knowledge bases. We show that also in this setting monitors can effectively be constructed. The (double-exponential) size of the constructed monitors is in fact optimal, and not higher than in the propositional case. As an auxiliary result, we show how to construct Büchi automata for ALC-LTL-formulae, which yields alternative proofs for the known upper bounds of deciding satisfiability in ALC-LTL.
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Moreno-Castro, C., and M. Crespo. IBERIFIER Reports: The Impact of Disinformation on the Media Industry in Spain and Portugal. Servicio de Publicaciones de la Universidad de Navarra, 2023. http://dx.doi.org/10.15581/026.001.

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Disinformation, the deliberate spread of false or misleading information, has become an increasingly pressing issue in today’s society. The media industry, which plays a critical role in providing reliable and accurate information to the public, has been significantly impacted by the rise of disinformation. This IBERIFIER Report provides an analysis of the effects of disinformation on the media industry and the challenges it poses for journalists, media organizations, and the public. It highlights the erosion of public trust in the media, the need for journalists to verify information more rigorously, and the creation of a market for sensationalist and biased news. The researchers from IBERIFIER surveyed the Spanish and Portuguese population to analyze their response to disinformation and misinformation, their trust in media outlets, and their perception of media verification procedures. Data shows that both countries had high trust in health institutions, and both achieved high rates of complete vaccination among all population groups, especially the elderly and most vulnerable. Respondents from both countries trusted researchers, scientists, and experts the most, followed by journalists and doctors. However, respondents in Spain were skeptical about media paywalls and whether they prevented the dissemination of fake news. In Portugal, respondents showed a higher concern for disinformation in politics than among family members, colleagues, or friends. The survey analysis in Spain showed that gender influenced the loss of trust in media outlets that publish fake news, while the degree of trust in the media depended on the political party they voted for in the last elections. Media editors in both countries confirmed the importance of verification procedures, although there were differences in their approach. The report also suggests several solutions to combat disinformation, such as investing in media literacy programs, regulating online sources of disinformation, and promoting transparency and accuracy in reporting. By reading the report, policymakers, media organizations, and the general public can gain a better understanding of the effects of disinformation on the media industry in Spain and Portugal and the steps that can be taken to address this growing problem.
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