In this paper, a new Hidden Markov Model (HMM)-based face recognition system is proposed. As a novel point despite of five-state HMM used in pervious researches, we used 7-state HMM to cover more details. Indeed we add two new face regions, eyebrows and chin, to the model. As another novel point, we used a small number of quantized Singular Values Decomposition (SVD) coefficients as feature...

Previous work has reported the existence of "super-recognisers" (SRs), or individuals with extraordinary face recognition skills. However, the precise underpinnings of this ability have not yet been investigated. In this paper we examine (a) the face-specificity of super recognition, (b) perception of facial identity in SRs, (c) whether SRs present with enhancements in holistic processing and (...

From a user’s perspective, face recognition is one of the most desirable biometrics, due to its non-intrusive nature. As a large number of face recognition systems have been developed over the past 15 years, their evaluation and comparison by an independent body becomes crucial. Face Recognition Vendor Tests (FRVT) are organized at regular intervals by the National Institute of Standards and Te...

Face recognition, holistic processing, and processing of configural and featural facial information are known to be influenced by face race, with better performance for own- than other-race faces. However, whether these various other-race effects (OREs) arise from the same underlying mechanisms or from different processes remains unclear. The present study addressed this question by measuring t...

Face recognition is widely held to rely on 'configural processing', an analysis of spatial relations between facial features. We present three experiments in which viewers were shown distorted faces, and asked to resize these to their correct shape. Based on configural theories appealing to metric distances between features, we reason that this should be an easier task for familiar than unfamil...

This paper is based on a combination of the principal component analysis (PCA), eigenface and support vector machines. Using N-fold method and with respect to the value of N, any person’s face images are divided into two sections. As a result, vectors of training features and test features are obtain ed. Classification precision and accuracy was examined with three different types of kernel and...

HyperMask is a system which projects an animated face onto a physical mask, worn by an actor. As the mask moves within a prescribed area, its position and orientation are detected by a camera, and the projected image changes with respect to the viewpoint of the audience. The lips of the projected face are automatically synthesized in real time with the voice of the actor, who also controls the ...

automatic analysis of human facial expressions is one of the challenging problems in machine vision systems. it has many applications in human-computer interactions such as, social signal processing, social robots, deceit detection, interactive video and behavior monitoring. in this paper, we develop a new method for automatic facial expression recognition based on facial muscle anatomy and hum...

This paper describes the vision system for a humanoid robot, which includes the mechanism that controls eyeball orientation and blinking process. Along with the mechanism designed, the orientation of the camera, integrated with controlling servomotors. This vision system is a bio-mimic, which is  designed to match the size of human eye. This prototype runs face recognition and identifies, match...

this paper is based on a combination of the principal component analysis (pca), eigenface and support vector machines. using n-fold method and with respect to the value of n, any person’s face images are divided into two sections. as a result, vectors of training features and test features are obtain ed. classification precision and accuracy was examined with three different types of kernel and...