scholarly journals System for Face Recognition under Different Facial Expressions Using a New Associative Hybrid Model Amαβ-KNN for People with Visual Impairment or Prosopagnosia

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 578 ◽  
Author(s):  
Moisés Márquez-Olivera ◽  
Antonio-Gustavo Juárez-Gracia ◽  
Viridiana Hernández-Herrera ◽  
Amadeo-José Argüelles-Cruz ◽  
Itzamá López-Yáñez
Keyword(s):  
Face Recognition ◽  
Facial Expressions ◽  
Hybrid Model ◽  
Integrated System ◽  
K Nearest Neighbors ◽  
The People ◽  
Proposed Model ◽  
The Face ◽  
Controlled Environments ◽  
The Individual

Face recognition is a natural skill that a child performs from the first days of life; unfortunately, there are people with visual or neurological problems that prevent the individual from performing the process visually. This work describes a system that integrates Artificial Intelligence which learns the face of the people with whom the user interacts daily. During the study we propose a new hybrid model of Alpha-Beta Associative memories (Amαβ) with Correlation Matrix (CM) and K-Nearest Neighbors (KNN), where the Amαβ-CMKNN was trained with characteristic biometric vectors generated from images of faces from people who present different facial expressions such as happiness, surprise, anger and sadness. To test the performance of the hybrid model, two experiments that differ in the selection of parameters that characterize the face are conducted. The performance of the proposed model was tested in the databases CK+, CAS-PEAL-R1 and Face-MECS (own), which test the Amαβ-CMKNN with faces of subjects of both sexes, different races, facial expressions, poses and environmental conditions. The hybrid model was able to remember 100% of all the faces learned during their training, while in the test in which faces are presented that have variations with respect to those learned the results range from 95.05% in controlled environments and 86.48% in real environments using the proposed integrated system.

scholarly journals Who_Is : Identification system of human faces

2002 ◽  
Vol Volume 1, 2002 ◽  
Author(s):  
Mohamed Tayeb Laskri ◽  
Djallel Chefrour
Keyword(s):  
Face Recognition ◽  
Geometric Model ◽  
Personal Identification ◽  
Identification System ◽  
K Nearest Neighbors ◽  
City Block ◽  
The Face ◽  
Characteristic Points ◽  
The Individual ◽  
Application Fields

International audience Although human face recognition is a hard topic due to many parameters involved (e.g. variability of the position, lighting, hairstyle, existence of glasses, beard, moustaches, wrinkles...), it becomes of increasing interest in numerous application fields (personal identification, video watch, man machine interfaces...). In this work, we present WHO_IS, a system for person identification based on face recognition. A geometric model of the face is definedfrom a set of characteristic points which are extracted from the face image. The identification consists in calculating the K nearest neighbors of the individual test by using the City-Block distance. The system is tested on a sample of 100 people with a success rate of 86 %. Bien que la reconnaissance des visages humains soit un domaine difficile à cause de la multitude des paramètres qu'il faut prendre en compte (variation de posture, éclairage, style de coiffure, port de lunettes, de barbes, de moustaches, vieillesse…), il est très important de s'en intéresser vu les nombreux champs d'applications (vérification de personnes, télésurveillance, interfaces homme-machine …). Dans ce travail nous présentons la mise en œuvre de WHO_IS, un système d'identification de personnes par reconnaissance des visages humains. Nous avons développé un modèle géométrique du visage basé sur un ensemble de points caractéristiques extraits à partir de l'image du visage. La procédure d'identification consiste à calculer les K plus proches voisins de l'individu test dans le sens de la distance City-Block. Le système WHO_IS a été testé sur un échantillon de 100 personnes. Un taux de reconnaissance correcte de 86% a été obtenu

scholarly journals Web Application for Emotion-based Music Player

2021 ◽  
Vol 9 (12) ◽  
pp. 11-14
Author(s):  
Kamal Naina Soni
Keyword(s):  
Computer Vision ◽  
Human Brain ◽  
Facial Expressions ◽  
Web Application ◽  
Emotional State ◽  
Current State ◽  
The Face ◽  
Current Mood ◽  
The Individual ◽  
Music Player

Abstract: Human expressions play an important role in the extraction of an individual's emotional state. It helps in determining the current state and mood of an individual, extracting and understanding the emotion that an individual has based on various features of the face such as eyes, cheeks, forehead, or even through the curve of the smile. A survey confirmed that people use Music as a form of expression. They often relate to a particular piece of music according to their emotions. Considering these aspects of how music impacts a part of the human brain and body, our project will deal with extracting the user’s facial expressions and features to determine the current mood of the user. Once the emotion is detected, a playlist of songs suitable to the mood of the user will be presented to the user. This can be a big help to alleviate the mood or simply calm the individual and can also get quicker song according to the mood, saving time from looking up different songs and parallel developing a software that can be used anywhere with the help of providing the functionality of playing music according to the emotion detected. Keywords: Music, Emotion recognition, Categorization, Recommendations, Computer vision, Camera

The Face Revisited: Using Deleuze and Guattari to Explore the Politics of Algorithmic Face Recognition

2019 ◽  
Vol 37 (1) ◽  
pp. 73-91
Author(s):  
Claudio Celis Bueno
Keyword(s):  
Face Recognition ◽  
Gilles Deleuze ◽  
The Political ◽  
Deleuze And Guattari ◽  
Political Dimension ◽  
The Face ◽  
The Individual ◽  
Clear Relation

This article explores the political dimension of algorithmic face recognition through the prism of Gilles Deleuze and Félix Guattari’s notion of faciality. It argues that algorithmic face recognition is a technology that expresses a key aspect of contemporary capitalism: the problematic position of the individual in light of new forms of algorithmic and statistical regimes of power. While there is a clear relation between modern disciplinary mechanisms of individualization and the face as a sign of individuality, in control societies this relation appears more as a contradiction. The article contends that Deleuze and Guattari’s concepts of machinic enslavement and social subjection offer a fruitful perspective from where to identify the power mechanisms behind the problematic position of the individual in the specific case of algorithmic face recognition.

Robust and discriminative dictionary learning for face recognition

2018 ◽  
Vol 16 (02) ◽  
pp. 1840004 ◽  
Author(s):  
Guojun Lin ◽  
Meng Yang ◽  
Linlin Shen ◽  
Mingzhong Yang ◽  
Mei Xie
Keyword(s):  
Face Recognition ◽  
Facial Expressions ◽  
Dictionary Learning ◽  
State Of The Art ◽  
Face Image ◽  
Superior Performance ◽  
Face Images ◽  
Proposed Model ◽  
Classification Capability ◽  
Discriminative Dictionary Learning

For face recognition, conventional dictionary learning (DL) methods have some disadvantages. First, face images of the same person vary with facial expressions and pose, illumination and disguises, so it is hard to obtain a robust dictionary for face recognition. Second, they don’t cover important components (e.g., particularity and disturbance) completely, which limit their performance. In the paper, we propose a novel robust and discriminative DL (RDDL) model. The proposed model uses sample diversities of the same face image to learn a robust dictionary, which includes class-specific dictionary atoms and disturbance dictionary atoms. These atoms can well represent the data from different classes. Discriminative regularizations on the dictionary and the representation coefficients are used to exploit discriminative information, which improves effectively the classification capability of the dictionary. The proposed RDDL is extensively evaluated on benchmark face image databases, and it shows superior performance to many state-of-the-art dictionary learning methods for face recognition.

scholarly journals Novel Descriptors for Effective Recognition of Face and Facial Expressions

2020 ◽  
Vol 34 (5) ◽  
pp. 521-530
Author(s):  
Farid Ayeche ◽  
Adel Alti
Keyword(s):  
Face Recognition ◽  
Facial Expressions ◽  
Support Vector Machine Classifier ◽  
Recognition Rate ◽  
Face Image ◽  
Support Vector ◽  
Expression Recognition ◽  
The Face ◽  
Public Datasets ◽  
Edge Response

In this paper, we present a face recognition approach based on extended Histogram Oriented Gradient (HOG) descriptors to extract the facial expressions features allowing classifying the faces and facial expressions. The approach is based on determining the different directional codes on the face image based on edge response values to define the feature vector from the face image. Its size is reduced to improve the performance of the SVM (Support Vector Machine) classifier. Experiments are conducted using two public datasets: JAFFE for facial expression recognition and YALE for face recognition. Experimental results show that the proposed descriptor achieves recognition rate of 92.12% and execution time ranging from 0.4s to 0.7s in all evaluated databases compared with existing works. Experiments demonstrate and confirm both the effectiveness and the efficiency of the proposed descriptor.

A Review on Biometric Technology

2018 ◽  
Vol 8 (4) ◽  
pp. 101
Author(s):  
Kartik Choudhary ◽  
Rizwan Khan
Keyword(s):  
Face Recognition ◽  
Iris Recognition ◽  
Review Paper ◽  
Behavioral Characteristics ◽  
Biometric System ◽  
Biometric Technology ◽  
The Face ◽  
The Individual ◽  
Recognition Technique ◽  
Better Than

Biometric Technology has turned out to be a popular area of research in computer vision and one of the most successful applications for identifying humans by capturing and analysing the sole feature or characteristic of   individual which is possessed by them and involves their Physical and Behavioral characteristics. For the individual validation and authentication the biometric system has this responsibility. Biometric Technology started from the fingerprints recognition and later on improvements were done in it to make it more secure which involves the face recognition and iris Recognition. Almost both of them are available and regarded as the accurate and reliable technology for biometric validation system. This review paper is all about Face recognition techniques in biometric locking system and Iris recognition technique of identification and the ways of making locking systems ways more efficient, full of ease, more secure, and far better than before so as to make locking or security stronger. It discusses about face recognition technique, its working and its application in different sector along with iris recognition, its working, its application.

Craft and Artisan Initiatives of the Salvadoran Civil War (1980–1992)

2020 ◽  
Vol 6 (1) ◽  
pp. 37-56
Author(s):  
Emilio Velis ◽  
Kate Samson ◽  
Isaac Robles ◽  
Daniel Rodríguez
Keyword(s):  
Civil War ◽  
Traumatic Experiences ◽  
Arts And Crafts ◽  
Social Unrest ◽  
The People ◽  
Maker Culture ◽  
The Face ◽  
Inclusive Concept ◽  
The Individual ◽  
Salvadoran Civil War

Abstract This article describes the testimonies of two arts and crafts collectives during the Salvadoran Civil War in the 1980s. These collectives, open to victims and refugees of the war, emerged as creative spaces during a time of significant social unrest. As participants learned to make and produce arts and crafts, these activities encouraged individual expression and allowed them to heal traumatic experiences. By describing the aspects that motivated and discouraged the involvement of participants over time, we show how the individual and collective aspects of making are important for the sustained participation of the people who engage in maker culture. We draw comparisons between the struggles of these historical movements and of current embodiments of the maker culture, in order to draw conclusions regarding how making can be a personal catalyst in the face of social hardship, the importance of economic sustainability in maker initiatives and how unjust gender dynamics take place in these spaces. The ability to compare and learn from these historical initiatives serves to unpack maker culture as a social asset that can be described beyond the mere use of digital tools and to repurpose it as a more inclusive concept that takes into account narratives from a broader range of expressions of making.

scholarly journals ROBUST REPRESENTATION OF 3D FACES FOR RECOGNITION

2006 ◽  
Vol 20 (08) ◽  
pp. 1159-1186 ◽  
Author(s):  
A. BELÉN MORENO ◽  
ÁNGEL SÁNCHEZ ◽  
ENRIQUE FRÍAS-MARTÍNEZ
Keyword(s):  
Face Recognition ◽  
Facial Expressions ◽  
Facial Recognition ◽  
Recognition Rate ◽  
Relevant Information ◽  
Large Set ◽  
Discrimination Power ◽  
3D Face ◽  
The Face ◽  
The Difference

Automatic face recognition is becoming increasingly important due to the security applications derived from it. Although the facial recognition problem has focused on 2D images, recently, due to the proliferation of 3D scanning hardware, 3D face recognition has become a feasible application. This 3D approach does not need any color information. In this way, it has the following main advantages in comparison to more traditional 2D approaches: (1) being robust under lighting variations and (2) providing more relevant information. In this paper we present a new 3D facial model based on the curvature properties of the surface. Our system is able to detect the subset of the characteristics of the face with higher discrimination power from a large set. The robustness of the model is tested by comparing recognition rates using both controlled and noncontrolled environments regarding facial expressions and facial rotations. The difference between the recognition rates of the two environments of only 5% proves that the model has a high degree of robustness against pose and facial expressions. We consider that this robustness is enough to implement facial recognition applications, which can achieve up to 91% correct recognition rate. A publish 3D face database containing face rotations and expressions has been created to achieve the recognition experiments.

scholarly journals Acceptance of cloud computing in the Malaysian public sector: A proposed model

2019 ◽  
Vol 11 ◽  
pp. 184797901988070 ◽  
Author(s):  
Mohd Talmizie Amron ◽  
Roslina Ibrahim ◽  
Nur Azaliah Abu Bakar ◽  
Suriayati Chuprat
Keyword(s):  
Cloud Computing ◽  
Public Sector ◽  
Technological Factor ◽  
The Public ◽  
Use Of Technology ◽  
The People ◽  
Proposed Model ◽  
Government Project ◽  
The Individual ◽  
The Impact

The Malaysian government has initiated a cloud government project as an integration of cloud computing and unified communication-based applications toward the digital and cloud work environment. However, the impact studies have found that the implementation of this project has several weaknesses such as lack of infrastructure support, weak IT knowledge, and lack of awareness among public sector employees causing applications not to be fully utilized. Therefore, it is crucial to conduct a study to measure the acceptance of government cloud project because there has been much investment in the project. This study applied Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Readiness Index (TRI) and several factors to develop the research model which is divided into two main factors: technological and human. The technological factor might determine the likelihood of its acceptance by the public sector and might stimulate them to accept it. The human factor as the characteristics of the people in the public sector that may contribute to creating the need for and ability to accept cloud computing. This proposed model will be used to evaluate the individual acceptance of cloud computing in the Malaysian public sector. For future work, this model needs to be enriched with interview sessions and quantitative surveys to validate the findings.

scholarly journals Age-based facial recognition using convoluted neural network deep learning algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 424
Author(s):  
Julius Yong Wu Jien ◽  
Aslina Baharum ◽  
Shaliza Hayati A. Wahab ◽  
Nordin Saad ◽  
Muhammad Omar ◽  
...  
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Learning Algorithm ◽  
Facial Recognition ◽  
Well Being ◽  
Deep Learning Algorithm ◽  
Business Applications ◽  
Image Dataset ◽  
The Face ◽  
The Individual

Face recognition is the use of biometric innovations that can see or validate a person by seeing and investigating designs depending on the shape of the individual. Face recognition is used largely for the purpose of well-being, despite the fact that passion for different areas of use is growing. Overall, face recognition innovations are worth considering because they have the potential for broad legal jurisdiction and different business applications. It is widely used in many spaces. How it works is a product of facial recognition processing facial geometry. The hole between the ear and the good way from the front to the jaw are the main variables. This code distinguishes the highlight of the face that is important for your facial separation and creates your facial expression. Therefore, this study gives an overview of age detection using a different combination of machine learning and image processing methods on the image dataset.

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