Linear Discriminant Analysis (LDA) Linear Discriminant Analysis (LDA), also known as Fisherface method, uses the Fisher’s linear discriminant criterion to overcome the limitations of eigenfaces method (Batagelj, 2006). This criterion tries to maximize the ratio of the determinant of the between-class scatter matrix of the projected samples to the determinant of the within-class scatter matrix of the projected samples. The aim is to maximize the between-class scatter while minimizing the within-class scatter. This approach includes two processes, training and classification (Chelali, Djeradi & Dejradi, 2009). In the training process, a subspace will be established by using the training samples, and then the training faces will be projected onto the same subspace. In the classification process, the input face image will be measured by Euclidean Distance to the subspace, and a decision will be made, either accept or reject. Background and Related Work Fisher discriminants group images of the same space and separates images of different classes (Delac, Grgic, 2006). Images are projected from N2 dimensional space to C dimensional space that are projected onto a single line. Depending on the direction of the line, the points can either be mixed together, or separated (Batagelj, 2006). Figure1: The points are mixed together Figure2: The points are separated Fisher discriminants find the line that best separates the points. To identify an input test image, the projected test image is compared to each projected training image, and the test image is identified as the closest training image (Zhao, Chellappa & Phillips, 1999). As with eigenspace projection, training images are projected into a subspace. The te... ... middle of paper ... ... analysis for face recognition. (Master's thesis), Available from IEEE. (978-1-4244-3757-3/09/). [2] Kresimir Delac, Mislav Grgic, Sonja Grgic. (2006). Independent comparative Study of PCA, ICA and LDA on the FERET data Set. Wiley periodicals,Inc. vol15,p252-260. [3] W. Zhao, R. Chellappa and P. J. Phillips, (April 1999). Subspace Linear Discriminant Analysis for Face Recognition. Tech. rep. CAR-TR-914, Center for Automation Research, University of Maryland, College Park, MD. [4] Borut Batagelj, (May 2006). Face recognition in different subspaces - A comparative study”, 6th International Workshop on Pattern Recognition in Information Systems, PRIS 2006 in conjunction with ICEIS 2006, Paphos, Cyprus. [5] Kresimir Delac, Mislav Grgic, Panos Liatsis. (March 2005). Appearance based statistical methods for face recognition. The 47th international symposium EL, Croatia.
The concept of face is referring to the socially approved self-image. It is about honor and shame belief and value systems. Facework is the verbal and nonverbal interactions we use in regards to our own social self-image and the social image of others.
Biometrics-based authentication applications include workstation, network, and domain access, single sign-on, application logon, data protection, remote access to resources, transaction security and Web security (Campbell, 1995). Utilized alone or integrated with other technologies such as smart cards, encryption keys and digital signatures, biometrics are set to pervade nearly all aspects of the economy and our daily lives (Campbell, 1995). Among the features measured are; face, fingerprints, hand geometry, iris, and voice (Campbell, 1995).
To test these hypotheses, we first collected a two point discriminator containing a variety of distances for two points. The point distances on the discriminator included values of.25 millimeters being the smallest, ...
The term biometrics is commonly known as the field of development of statistical and mathematical methods applicable to data analysis problems in the biological sciences. Though, even more recently it has taken on a whole new definition. Biometrics is an amazing new topic referring to “the emerging field of technology devoted to the identification of individuals using biological traits, based on retinal or iris scanning, fingerprints, or face recognition”. Biometrics has already begun using applications that range from attendance tracking with a time clock to security checkpoints with a large volume of people. The growing field of biometrics has really been put on the map by two things, the technological advances made within the last 20 years, and the growing risk of security and terrorism among people all over the world. In this paper I will focus on: the growing field of biometrics, why it is important to our future, how the United States government has played a role in its development and use, the risks involved, the implications on public privacy, and further recommendations received from all over the science and technology field.
...face reveals: basic and applied studies of spontaneous expression using the facial action coding system (FACS). 2nd ed 2. Oxford: Oxford University Press
Biometrics is described as the use of human physical features to verify identity and has been in use since the beginning of recorded history. Only recently, biometrics has been used in today’s high-tech society for the prevention of identity theft. In this paper, we will be understanding biometrics, exploring the history of biometrics, examples of today’s current technology and where biometrics are expected to go in the future.
Principal Component Analysis (PCA) is a multivariate analysis performed in purpose of reducing the dimensionality of a multivariate data set in order to recognize the shape or pattern of that data set. In other words, PCA is a powerful technique for pattern recognition that attempts to explain the variance of a large set of inter-correlated variables. It indicates the association between variables, thus, reducing the dimensionality of the data set. (Helena et al, 2000; Wunderlin et al, 2001; Singh et al, 2004)
Lyons et al. [6] Classifying facial attributes using a 2-D Gabor wavelet representation and discriminant analysis used a set of multi scale, multi orientation Gabor filters to transform the images first. The Gabor coef...
When Maxwell Smart first whipped out his shoe phone in 1965, everyone saw an act of pure movie magic. Back in the mid to late 1900s everybody had the same idea of the future. Everyone pictured the future as talking robots (Siri), computerized pocket-sized dictionaries (smart-phones), hovering devices (drones), and much more. Today, everyone thinks of these technologies as commonalities. Most of these current devices have a valuable impact, while few create debatable issues. The company NGI has a system that will revolutionize the field of biometric facial recognition. In the article titled Embracing Big Brother: How Facial Recognition Could Help Fight Crime, author Jim Stenman says, "The mission is to reduce terrorist and criminal activity by improving and expanding biometric identification as well as criminal history information s...
Signal detection theory is introduced by mathematicians and engineer in 1950 . It started to evolve from the developing electronics communication.
Biometric technology is used for the ways humans can be identified by unique aspects of their bodies, such as fingerprints, body odor, our voices and many more. If one was to think about privacy rights, he/she would be concerned about the widespread adoption of these systems, since such systems could easily be used to develop a record of known rebellious people and/or dangerous criminals, to be used for social control purposes. Although that may seem pretty good and a positive thing for the society, one should take into account of the defects and errors of technology. Of the many biometrics technologies that are being developed and are already developed, facial recognition is one of the most threatening because it can be deployed secretly; one may not know whether or when they can be caught in a surveillance camera for such facial recognition biometrics. Additionally, tests have found that the miscalculations for facial biometrics technologies are very high. As a result, according to Privacy Rights Clearinghouse, innocent people can be erroneously identified as dangerous criminals and actual dangerous criminals and/or suspected terrorists can fail to be detected overall, allowing for a huge injustice and unfairness. Privacy rights concerned with biometrics have sparked a concern and should be dealt with; otherwise, this is just one of the
The last step of our proposed system is classification of face emotions. The information extracted from previous stage will serve as input for neural network to recognize the face expressions. The architecture is showed at Figure 3.9. We will use this method in order to find out a mapping between the geometric and appearance features. The features then will be combined as the hidden neural by using Gaussian function and six output of neurons will be generated which are representing as sadness, fear, angry, happy, disgust, and surprise.
“The term -information security- means protecting information and information systems from unauthorized access, use, disclosure, disruption, modification, or destruction” (United States Code, 2008). In order to ensure the identity of who is trying to access the information, the concept of “Biometric Technology” has been developed in the last years. This essay will start explaining this concept and the characteristics of its development through the time. Then, the essay will offer a brief explanation of biometric systems operation and a description of different biometric systems developed until now. Finally, this research analyzes the current and future applications and the issues that surround it.
If any area of research is going to hold a genetic basis, facial recognition in children is going to. It is the beginnings of attachment, the basis of social interaction and is vital for infant and caregiver interaction. Therefore it would be obvious that such a skill would have the possibilities to be innate, however new research suggest that this it is also genetic. After Thomas’ researched the theory, he suggested that even with all other variables taken into consideration, there is unlikely to be any variation let to attribute to no familial environment rendering face recognition ability essentially all genetic. It’s not just the ‘normal’ ...
Computerized facial recognition is an old idea conceived decades ago, but the use of it has accelerated since the 1990s, due to cheaper technology and...