scholarly journals Past, Present, and Future of Face Recognition: A Review

2020 ◽  
Author(s):  
Insaf Adjabi ◽  
Abdeldjalil Ouahabi ◽  
Amir Benzaoui ◽  
Abdelmalik Taleb-Ahmed
Keyword(s):  
Face Recognition ◽  
Ethical Issues ◽  
Ambient Conditions ◽  
Expression Change ◽  
Research Fields ◽  
3D Data ◽  
Angle Of View ◽  
Active Research ◽  
Degree Of Maturity ◽  
Commercial Applications

Face recognition is one of the most active research fields of computer vision and pattern recognition, with many practical and commercial applications including identification, access control, forensics, and human-computer interactions. However, identifying a face in a crowd raises serious questions about individual freedoms and poses ethical issues. Significant methods, algorithms, approaches, and databases have been proposed over recent years to study constrained and unconstrained face recognition. 2D approaches reached some degree of maturity and reported very high rates of recognition. This performance is achieved in controlled environments where the acquisition parameters are controlled, such as lighting, angle of view, and distance between the camera-subject. However, if the ambient conditions (e.g., lighting) or the facial appearance (e.g., pose or facial expression) change, this performance will degrade dramatically. 3D approaches were proposed as an alternative solution to the problems mentioned above. The advantage of 3D data lies in its invariance to pose and lighting conditions, which has enhanced recognition systems efficiency. 3D data, however, is somewhat sensitive to changes in facial expressions. This review presents the history of face recognition technology, the current state-of-the-art methodologies, and future directions. We specifically concentrate on the most recent databases, 2D and 3D face recognition methods. Besides, we pay particular attention to deep learning approach as it presents the actuality in this field. Open issues are examined and potential directions for research in facial recognition are proposed in order to provide the reader with a point of reference for topics that deserve consideration.

scholarly journals Past, Present, and Future of Face Recognition: A Review

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1188 ◽  
Author(s):  
Insaf Adjabi ◽  
Abdeldjalil Ouahabi ◽  
Amir Benzaoui ◽  
Abdelmalik Taleb-Ahmed
Keyword(s):  
Face Recognition ◽  
Ethical Issues ◽  
Ambient Conditions ◽  
Expression Change ◽  
Research Fields ◽  
3D Data ◽  
Angle Of View ◽  
Active Research ◽  
Degree Of Maturity ◽  
Commercial Applications

Face recognition is one of the most active research fields of computer vision and pattern recognition, with many practical and commercial applications including identification, access control, forensics, and human-computer interactions. However, identifying a face in a crowd raises serious questions about individual freedoms and poses ethical issues. Significant methods, algorithms, approaches, and databases have been proposed over recent years to study constrained and unconstrained face recognition. 2D approaches reached some degree of maturity and reported very high rates of recognition. This performance is achieved in controlled environments where the acquisition parameters are controlled, such as lighting, angle of view, and distance between the camera–subject. However, if the ambient conditions (e.g., lighting) or the facial appearance (e.g., pose or facial expression) change, this performance will degrade dramatically. 3D approaches were proposed as an alternative solution to the problems mentioned above. The advantage of 3D data lies in its invariance to pose and lighting conditions, which has enhanced recognition systems efficiency. 3D data, however, is somewhat sensitive to changes in facial expressions. This review presents the history of face recognition technology, the current state-of-the-art methodologies, and future directions. We specifically concentrate on the most recent databases, 2D and 3D face recognition methods. Besides, we pay particular attention to deep learning approach as it presents the actuality in this field. Open issues are examined and potential directions for research in facial recognition are proposed in order to provide the reader with a point of reference for topics that deserve consideration.

scholarly journals Face recognition based on stable uniform patterns

2018 ◽  
Vol 7 (2) ◽  
pp. 626
Author(s):  
A. Mallikarjuna Reddy ◽  
V. Venkata Krishna ◽  
L. Sumalatha
Keyword(s):  
Face Recognition ◽  
Local Pattern ◽  
Feature Extraction Method ◽  
Image Histogram ◽  
Research Fields ◽  
Face Images ◽  
Wide Range ◽  
Robust Face Recognition ◽  
Active Research ◽  
Lbp Descriptor

Face recognition (FR) is one of the challenging and active research fields of image processing, computer vision and biometrics with numerous proposed systems. We present a feature extraction method named “stable uniform local pattern (SULP)”, a refined variant of ULBP operator, for robust face recognition. The SULP directly applied on gradient face images (in x and y directions) of a single image for capturing significant fundamental local texture patterns to build up a feature vector of a face image. Histogram sequences of SULP images of the two gradient images are finally concatenated to form the “stable uniform local pattern gradient (SULPG)” vector for the given image. The SULPG approach is experimented on Yale, ATT-ORL, FERET, CAS-PEAL and LFW face databases and the results are compared with the LBP model and various variants of LBP descriptor. The results indicate that the present descriptor is more powerful against a wide range of challenges, such as illumination, expression and pose variations and outperforms the state-of-the-art methods based on LBP.

Social Movements in Latin America: Mapping the Literature

2020 ◽  
Author(s):  
Nicolás M. Somma
Keyword(s):  
Political Economy ◽  
Social Movements ◽  
Latin American ◽  
Transnational Activism ◽  
Organizational Fields ◽  
Family Labor ◽  
American Sociology ◽  
Research Fields ◽  
Vast Literature ◽  
Active Research

The study of social movements is currently one of the most active research fields in Latin American sociology. This article maps the vast literature on Latin American social movements (LASMs) from the late 1980s to the present. After briefly discussing how scholars have conceptualized LASMs, it presents seven influential approaches: structuralism, political economy, political context, organizational fields, “new social movements,” frames and emotions, and transnational activism. Then it discusses some works that zero in on the specificity of LASMs. It closes with a brief summary of the five coming chapters, each of which is devoted to a specific social movement “family”: labor, women’s, student, indigenous, and anti-globalization.

scholarly journals Magnon magic angles and tunable Hall conductivity in 2D twisted ferromagnetic bilayers

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Doried Ghader
Keyword(s):  
Band Structure ◽  
Magnetic Order ◽  
Condensed Matter ◽  
Twist Angle ◽  
Band Gaps ◽  
Novel Device ◽  
Flat Bands ◽  
Research Fields ◽  
Active Research ◽  
The Continuum

Abstract Twistronics is currently one of the most active research fields in condensed matter physics, following the discovery of correlated insulating and superconducting phases in twisted bilayer graphene (tBLG). Here, we present a magnonic analogue of tBLG. We study magnons in twisted ferromagnetic bilayers (tFBL) with collinear magnetic order, including exchange and weak Dzyaloshinskii-Moriya interactions (DMI). For negligible DMI, tFBL presents discrete magnon magic angles and flat moiré minibands analogous to tBLG. The DMI, however, changes the picture and renders the system much more exotic. The DMI in tFBL induces a rich topological magnon band structure for any twist angle. The twist angle turns to a control knob for the magnon valley Hall and Nernst conductivities. Gapped flat bands appear in a continuum of magic angles in tFBL with DMI. In the lower limit of the continuum, the band structure reconstructs to form several topological flat bands. The luxury of twist-angle control over band gaps, topological properties, number of flat bands, and valley Hall and Nernst conductivities renders tFBL a novel device from fundamental and applied perspectives.

scholarly journals Bypassing the Inertness of Aziridine/CO2 Systems to Access 5-Aryl-2-Oxazolidinones: Catalyst-Free Synthesis Under Ambient Conditions

2020 ◽  
Author(s):  
Giulio Bresciani ◽  
Emanuele Antico ◽  
Gianluca Ciancaleoni ◽  
Stefano Zacchini ◽  
Guido Pampaloni ◽  
...  
Keyword(s):  
Activation Barrier ◽  
Research Area ◽  
Ambient Conditions ◽  
Nmr Studies ◽  
Co Catalyst ◽  
Critical Issues ◽  
High Activation Barrier ◽  
Sequential Addition ◽  
Synthetic Routes ◽  
Active Research

The development of sustainable synthetic routes to access valuable oxazolidinones via CO<sub>2</sub> fixation is an active research area, and the aziridine/carbon dioxide coupling has aroused a considerable interest. This reaction is featured by a high activation barrier, so to require a catalytic system, and may present some other critical issues. Here, we describe the straightforward gram-scale synthesis of a series of 5-​aryl-​2-oxazolidinones at ambient temperature and atmospheric CO<sub>2</sub> pressure, in the absence of any catalyst/co-catalyst. The key to this innovative procedure consists in the direct transfer of the pre-formed amine/CO<sub>2</sub> adduct (carbamate) to common aziridine precursors (dimethylsulfonium salts), replacing the classical sequential addition of amine (intermediate isolation of aziridine) and then CO<sub>2</sub>. The reaction mechanism has been investigated by NMR studies and DFT calculations applied to model cases.<br>

Action Recognition

2010 ◽  
pp. 228-243
Author(s):  
Qingdi Wei ◽  
Xiaoqin Zhang ◽  
Weiming Hu
Keyword(s):  
Action Recognition ◽  
Mean Shift ◽  
Human Action ◽  
Shape Context ◽  
Research Fields ◽  
Dominant Set ◽  
Novel Method ◽  
Active Research ◽  
Context Features ◽  
Human Silhouette

Action recognition is one of the most active research fields in computer vision. This chapter first reviews the action recognition methods in literature from two aspects: action representation and recognition strategy. Then, a novel method for classifying human actions from image sequences is investigated. In this method, each human action is represented by a sequence of shape context features of human silhouette during the action, and a dominant set-based approach is employed to classify the action to the predefined classes. The dominant set-based approach to classification is compared with K-means, mean shift, and Fuzzy-Cmean approaches.

Intensity-Based Classification and Related Methods in Brain MR Images

2016 ◽  
pp. 78-105
Author(s):  
Luminita Moraru ◽  
Simona Moldovanu ◽  
Anjan Biswas
Keyword(s):  
Image Processing ◽  
Clustering Algorithms ◽  
Magnetic Resonance Images ◽  
Specific Reference ◽  
Research Fields ◽  
Technical Developments ◽  
Highly Active ◽  
The Subject ◽  
Active Research

Today, medical image processing and analysis are highly active research fields boosted by rapid technical developments in medical imaging field. This chapter describes common procedures such as thresholding methods and clustering algorithms (both non-hierarchical and hierarchical approaches) used for digital image processing, with specific reference to brain magnetic resonance images. These techniques represent starting points for other sophisticated methods such as segmentation and classification. The results, which are an outcome of these methods, are used for classification of neurodegenerative diseases such as Alzheimer, Pick's, Huntington's or cerebral calcinosis. A number of applications together with the code listing are provided with the aim to make the subject accessible and practical. The MATLAB software will help the readers to identify and choose the best solution for a particular problem.

Hausdorff Distance for Face Recognition

2015 ◽  
pp. 39-46
Keyword(s):  
Face Recognition ◽  
Hausdorff Distance ◽  
Similarity Measures ◽  
Face Verification ◽  
3D Data ◽  
Modified Hausdorff Distance

When two sets are differently sized, the Hausdorff distance can be computed between them, even if the cardinality of one set is infinite. Different versions of this distance have been proposed and employed for face verification, among which the modified Hausdorff distance is the most famous. The important point to be noted is that, among the most commonly used similarity measures, the Hausdorff distance is the only one that has been widely applied to 3D data.

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