Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. In cortical area V1 exist double-opponent colour blobs, also simple, complex and end-stopped cells which provide input for a multiscale line/edge representation, keypoints for dynamic routing and saliency maps for Focus-of-Attention. All these combined allow us to segrega...

3D face recognition is a promising alternative to face the problem of recognizing 2D robustness. Therefore, the main advantage of 3D face recognition-based approach uses all the information on the geometry of the face, which allows us to get an accurate representation of the face. In the proposing contribution all distinctive facial features are captured by first extracting SIFT (Scale Invarian...

This paper presents real time face detection and recognition system and also an efficient technique to train the database. The algorithm used is of stereo-face detection in video sequences. A stereo face is a face of man presented by the set of images obtained from different points of views such data can be used for face of man presented by the set of images obtained from different points of vi...

Effects of shading in face recognition have often alluded to 3D shape processing. However, research to date has failed to demonstrate any use of important 3D information. Stereopsis adds no advantage in face encoding [Liu, C. H., Ward, J., & Young, A. W. (in press). Transfer between 2D and 3D representations of faces. Visual Cognition], and perspective transformation impairs rather than assists...

Face recognition in video has gained wide attention due to its role in designing surveillance systems. One of the main advantages of video over still frames is that evidence accumulation over multiple frames can provide better face recognition performance. However, surveillance videos are generally of low resolution containing faces mostly in non-frontal poses. Consequently, face recognition in...

This paper presents a novel approach to aid face recognition: Using multiple views of a face, we construct a 3D model instead of directly using the 2D images for recognition. Our framework is designed for videos, which contain many instances of a target face from a sequence of slightly differing views, as opposed to a single static picture of the face. Specifically, we reconstruct the 3D face s...

In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical application. Many recent events, such as terrorist attacks, have exposed the serious weaknesses in most sophisticated security systems. Automatic face recognition has long been established as one of the most active research areas in c...

In recent years, 3D face recognition has been considered as a major solution to deal with these unsolved issues of reliable 2D face recognition, i.e. illumination and pose variations. This paper focuses on two critical aspects of 3D face recognition: facial feature description and classifier design. To address the former one, a novel local descriptor, namely Local Shape Patterns (LSP), is propo...

Machine vision will play a significant role in the next generation of IR 4.0 systems. Recognition and analysis faces are essential many vision-based applications. Deep Learning provides thrust for advancement visual recognition. An important tool recognition tasks is Convolution Neural networks (CNN). However, 2D methods machine suffer from Pose, Illumination, Expression (PIE) challenges occlus...

In this paper, we present a new 3D dynamic face dataset dedicated to the development and test of algorithms which target face recognition under unconstrained conditions, from 3D videos. Several challenges which can occur in real world like scenarios are considered, such as continuous and freely-pose variation, expressive and talking faces, changes of the distance to the 3D camera, occlusions an...