Abstract— Face is the most common biometric used by humans, its applications range from static, mug-shot verification to a dynamic, uncontrolled face identification in a cluttered background. The main objective of this paper is to construct an effective human face identification system. The presented algorithm combines the scaling process, histogram equalization process, wavelet transform proce...

Brain-damaged patients experience difficulties in recognizing a face (prosopagnosics), but they can still recognize its expression. The dissociation between these two face-related skills has served as a keystone of models of face processing. We now report that the presence of a facial expression can influence face identification. For normal viewers, the presence of a facial expression influence...

Looking at our face in a mirror is one of the strongest phenomenological experiences of the Self in which we need to identify the face as reflected in the mirror as belonging to us. Recent behavioral and neuroimaging studies reported that self-face identification not only relies upon visual-mnemonic representation of one's own face but also upon continuous updating and integration of visuo-tact...

Great progress in face recognition technology has been made recently. Since the first face recognition vendor test (FRVT)Phillips et al. (2007) in 1993, face recognition performance has been improved by two orders of magnitude in thirteen years. Notably, in the FRVT 2006 it is the first time that algorithms are capable of human performance levels, and at false acceptance rates in the range of 0...

Human facial images provide the demographic information, such as ethnicity and gender. Conversely, ethnicity and gender also play an important role in face-related applications. Image-based ethnicity identification problem is addressed in a machine learning framework. The Linear Discriminant Analysis (LDA) based scheme is presented for the two-class (Asian vs. non-Asian) ethnicity classificatio...

∗ Analogical & Neural Computing Laboratory Computer and Automation Research Institute Lágymányosi u. 11, Budapest, H-1111, Hungary, e-mail: [szlavik,sziranyi]@sztaki.hu, tel.: +36 1 279 7155 Abstract In this paper an analogic face-registration algorithm is proposed for video tracking of surveillance applications using CNN-UM. The algorithm follows pose variations of head by affine transformatio...

In this article, we propose a robust person identification algorithm in video that is able to detect and identify faces. The method we have developed combines approaches for detection and recognition using an efficient correlation technique and auto associative neural network. The experiments confirm the robustness of our approach against occlusion and illumination changes.

Robust face identification system in complex airport environment, which can identify certain candidates from a crowd of people in real time, is in urgent demand. S-AdaBoost is discussed in this paper as a variant of AdaBoost to handle real world environment. The Face Identification System for Airports (F1SA), based upon SAdaBoost algorithm, is implemented in an international airport. Comparison...