This paper introduces a system in which the face recognition is carried out with the help of the local feature descriptors. As today face recognition is a very active area of research, a system which carries out the robust face recognition is needed to be developed. Face recognition is used in various fields of security and access control, surveillance military etc. here the system is developed...

Using functional magnetic resonance imaging (fMRI), we found an area in the fusiform gyrus in 12 of the 15 subjects tested that was significantly more active when the subjects viewed faces than when they viewed assorted common objects. This face activation was used to define a specific region of interest individually for each subject, within which several new tests of face specificity were run....

Most of human daily social interactions rely on the ability to successfully recognize faces. Yet ∼2% of the human population suffers from face blindness without any acquired brain damage [this is also known as developmental prosopagnosia (DP) or congenital prosopagnosia]). Despite the presence of severe behavioral face recognition deficits, surprisingly, a majority of DP individuals exhibit nor...

Two of the most robust markers for "special" face processing are the behavioral face-inversion effect (FIE)-the disproportionate drop in recognition of upside-down (inverted) stimuli relative to upright faces-and the face-selective fMRI response in the fusiform face area (FFA). However, the relationship between these two face-selective markers is unknown. Here we report that the behavioral FIE ...

This paper proposes a novel adaptive algorithm to extract facial feature points automatically such as eyebrows corners, eyes corners, nostrils, nose tip, and mouth corners in frontal view faces, which is based on cumulative histogram approach by varying different threshold values. At first, the method adopts the Viola-Jones face detector to detect the location of face and also crops the face re...

Theories of embodied cognition propose that recognizing facial expressions requires visual processing followed by simulation of the somatovisceral responses associated with the perceived expression. To test this proposal, we targeted the right occipital face area (rOFA) and the face region of right somatosensory cortex (rSC) with repetitive transcranial magnetic stimulation (rTMS) while partici...

system must be able to distinguish real face from a copy of face such as a photograph. In this paper, we propose a fast and memory efficient method of live face detection for embedded face recognition system, based on the analysis of the movement of the eyes. We detect eyes in sequential input images and calculate variation of each eye region to determine whether the input face is a real face o...

The face detection is process of detecting region of face from a picture of one or multiple persons together. The detected face is extracted in the proposed using the viola-Jones algorithm. The viola-Jones algorithm is considered effective in order to mark and extract the face features. The proposed model is using the correlation model for the purpose of the face recognition. The face recogniti...

In this work an effective face detector based on the well-known Viola-Jones algorithm is proposed. A common issue in face detection is that for maximizing the face detection rate a low threshold is used for classifying as face an input image, but at the same time using a low threshold drastically increases the number of false positives. In this paper several criteria are proposed for reducing f...

system must be able to distinguish real face from a copy of face such as a photograph. In this paper, we propose a fast and memory efficient method of live face detection for embedded face recognition system, based on the analysis of the movement of the eyes. We detect eyes in sequential input images and calculate variation of each eye region to determine whether the input face is a real face o...