Title of dissertation: FACE RECOGNITION AND VERIFICATION IN UNCONSTRAINED ENVIRIONMENTS Huimin Guo Doctor of Philosophy, 2012 Dissertation directed by: Professor Larry S. Davis Department of Computer Science Face recognition has been a long standing problem in computer vision. General face recognition is challenging because of large appearance variability due to factors including pose, ambient ...

Biometric identification system, which uses physical or behavioral features to check a person’s identity, ensures much greater security than passwords and number systems. Biometric features such as face or fingerprint can be stored on a microchip in credit card, for example. A single feature, however, sometimes fails to be exact enough to identification. Another disadvantage of using only one f...

After decades of research the notion that faces are special is still at the heart of heated debates. New techniques like brain imaging have advanced some of the arguments but empirical data from brain-damaged patients like paradoxical recognition effects have required more complex explanations aside from localisation of the face area in normal adults. In this paper we focus on configural face p...

The state-of-the-art of face recognition has been significantly advanced by the emergence of deep learning. Very deep neural networks recently achieved great success on general object recognition because of their superb learning capacity. This motivates us to investigate their effectiveness on face recognition. This paper proposes two very deep neural network architectures, referred to as DeepI...

RFID (Radio Frequency Identifier) and Biometric now a days are one of the most popular technologies in use today. This paper focuses on creating a MIS (Management Information S ystem) system of student using both RFID and biometric (face-detection) technology. With the increasing number of students managing the attendance manually becomes a tedious and risky job. With the evolution in technolog...

The use of biometric technique for automatic personal identification is one of the biggest challenges in the security field. The process is complex, because it is influenced by many factors related to the form, position, illumination, rotation, translation, disguise and occlusion of face characteristics. This work presents a searching method to identify a face in a training database. We have pr...

When complementary halves of different familiar faces are combined into a new face, there is interference in the identification of either half. This "composite face effect" has been taken as strong evidence that faces are processed holistically. Here, we demonstrate that this effect can persist when the two parts of a face are separated by up to 80 ms of visual noise, showing that the parts of ...

This article reviews conventional and novel methods for facial-image identification from forensic aspects. Among the conventional approaches, three methods, i.e., morphological comparison of facial features, anthropometric indices comparison, and face-to-face superimposition, are generally used. The methods most commonly used in caseworks are in the order of morphological comparison, anthropome...

Bilateral symmetry is a facial feature that plays an important role in the aesthetic judgments of faces. The extent to which symmetry contributes to the identification of faces is less clear. We investigated the relationship between facial asymmetry and identity using synthetic face stimuli where the geometric identity of the face can be precisely controlled. Thresholds for all observers were 2...