Mehdi Ghayoumi

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In this paper, we present an approach that unifies sub-space feature extraction and support vector classification for face recognition. Linear discriminant, independent component and principal component analyses are used for dimensionality reduction prior to introducing feature vectors to a support vector machine. The performance of the developed methods in(More)
Biometrics is the science and technology of measuring and analyzing biological data of human body for increasing systems security by providing accurate and reliable patterns and algorithms for person verification and identification and its solutions are widely used in governments, military and industries. Single source of information in biometric systems(More)
Previous approaches to model and analyze facial expression analysis use three different techniques: facial action units, geometric features and graph based modelling. However, previous approaches have treated these technique separately. There is an interrelationship between these techniques. The facial expression analysis is significantly improved by(More)
This paper describes a new automated facial expression analysis system that integrates Locality Sensitive Hashing (LSH) with Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) to improve execution efficiency of emotion classification and continuous identification of unidentified facial expressions. Images are classified using(More)
To protect user's information, computer systems utilize access control models. These models are supported by a set of policies defined by security administrators in the environment where the organization is active. In previous studies it has been shown that building a user interface that dynamically changes with the security policies defined for each user(More)
Template-Based face recognition methods have some limitation for the key points which are used for detection based on the common areas in facial images. One disadvantage of using a template-based method is that not all valuable key points are used. Nodes that are outside the areas that are sought with a template will be overlooked. Some of these key points(More)
Biometric data are the sensitive personal information and the large intra-class variability due to changes of the environment conditions is an issue in these type of data. Adaptive biometric is the solution that has been introduced and can make the systems more accurate and reliable. For this purpose, semi-supervised learning has been shown to be a possible(More)