scholarly journals Questionnaires or Inner Feelings: Who Measures the Engagement Better?

2020 ◽  
Vol 10 (2) ◽  
pp. 609
Author(s):  
Francesca Nonis ◽  
Elena Carlotta Olivetti ◽  
Federica Marcolin ◽  
Maria Grazia Violante ◽  
Enrico Vezzetti ◽  
...  
Keyword(s):  
New Product ◽  
User Engagement ◽  
Expression Recognition ◽  
Interaction Domain ◽  
Video Frames ◽  
Modeling Software ◽  
The Face ◽  
The Subject ◽  
Active Research

This work proposes an innovative method for evaluating users’ engagement, combining the User Engagement Scale (UES) questionnaire and a facial expression recognition (FER) system, active research topics of increasing interest in the human–computer interaction domain (HCI). The subject of the study is a 3D simulator that reproduces a virtual FabLab in which users can approach and learn 3D modeling software and 3D printing. During the interaction with the virtual environment, a structured-light camera acquires the face of the participant in real-time, to catch its spontaneous reactions and compare them with the answers to the UES closed-ended questions. FER methods allow overcoming some intrinsic limits in the adoption of questioning methods, such as the non-sincerity of the interviewees and the lack of correspondence with facial expressions and body language. A convolutional neural network (CNN) has been trained on the Bosphorus database (DB) to perform expression recognition and the classification of the video frames in three classes of engagement (deactivation, average activation, and activation) according to the model of emotion developed by Russell. The results show that the two methodologies can be integrated to evaluate user engagement, to combine weighted answers and spontaneous reactions and to increase knowledge for the design of the new product or service.

scholarly journals Klasifikasi Ketertarikan Belajar Anak PAUD Melalui Video Ekspresi Wajah Dan Gestur Menggunakan Convolutional Neural Network

2021 ◽  
Vol 10 (2) ◽  
pp. 182-188
Author(s):  
Ajeng Restu Kusumastuti ◽  
Yosi Kristian ◽  
Endang Setyati
Keyword(s):  
Neural Network ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Communication Skill ◽  
Early Age ◽  
Expression Recognition ◽  
The Face ◽  
Learning Interest ◽  
Learning Architectures

Abstract—The Covid-19 pandemic has transformed the offline education system into online. Therefore, in order to maximize the learning process, teachers were forced to adapt by having presentations that attract student's attention, including kindergarten teachers. This is a major problem considering the attention rate of children at early age is very diverse combined with their limited communication skill. Thus, there is a need to identify and classify student's learning interest through facial expressions and gestures during the online session. Through this research, student's learning interest were classified into several classes, validated by the teacher. There are three classes: Interested, Moderately Interested, and Not Interested. Trials to get the classification of student's learning interest by teacher validation, carried out by training and testing the cut area of the center of the face (eyes, mouth, face) to get facial expression recognition, supported by the gesture area as gesture recognition. This research has scenarios of four cut areas and two cut areas that were applied to the interest class that utilizes the weight of transfer learning architectures such as VGG16, ResNet50, and Xception. The results of the learning interest classification test obtained a minimum validation percentage of 70%. The result obtained through scenarios of three learning interest classes four cut areas using VGG16 was 75%, while for two cut areas using ResNet50 was 71%. These results proved that the methods of this research can be used to determine the duration and theme of online kindergarten classes.

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.

Adaptive Face Recognition of Partially Visible Faces

2012 ◽  
pp. 194-211
Author(s):  
T. Ravindra Babu ◽  
Chethan S.A. Danivas ◽  
S.V. Subrahmanya
Keyword(s):  
Face Recognition ◽  
Case Studies ◽  
Adaptive System ◽  
Research Area ◽  
Face Images ◽  
The Face ◽  
The Subject ◽  
Active Research ◽  
Partially Occluded ◽  
Active Research Area

Face Recognition is an active research area. In many practical scenarios, when faces are acquired without the cooperation or knowledge of the subject, they are likely to get occluded. Apart from image background, pose, illumination, and orientation of the faces, occlusion forms an additional challenge for face recognition. Recognizing faces that are partially visible is a challenging task. Most of the solutions to the problem focus on reconstruction or restoration of the occluded part before attempting to recognize the face. In the current chapter, the authors discuss various approaches to face recognition, challenges in face recognition of occluded images, and approaches to solve the problem. The authors propose an adaptive system that accepts the localized region of occlusion and recognizes the face adaptively. The chapter demonstrates through case studies that the proposed scheme recognizes the partially occluded faces as accurately as the un-occluded faces and in some cases outperforms the recognition using un-occluded face images.

Intensity-Based Classification and Related Methods in Brain MR Images

2017 ◽  
pp. 573-600
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.

scholarly journals 3D Approaches and Challenges in Facial Expression Recognition Algorithms—A Literature Review

2019 ◽  
Vol 9 (18) ◽  
pp. 3904 ◽  
Author(s):  
Francesca Nonis ◽  
Nicole Dagnes ◽  
Federica Marcolin ◽  
Enrico Vezzetti
Keyword(s):  
Facial Expression ◽  
Technological Development ◽  
Three Dimensional ◽  
3D Analysis ◽  
Expression Recognition ◽  
Interaction Domain ◽  
Still Images ◽  
Facial Expression Analysis ◽  
Viable Solution ◽  
Active Research

In recent years, facial expression analysis and recognition (FER) have emerged as an active research topic with applications in several different areas, including the human-computer interaction domain. Solutions based on 2D models are not entirely satisfactory for real-world applications, as they present some problems of pose variations and illumination related to the nature of the data. Thanks to technological development, 3D facial data, both still images and video sequences, have become increasingly used to improve the accuracy of FER systems. Despite the advance in 3D algorithms, these solutions still have some drawbacks that make pure three-dimensional techniques convenient only for a set of specific applications; a viable solution to overcome such limitations is adopting a multimodal 2D+3D analysis. In this paper, we analyze the limits and strengths of traditional and deep-learning FER techniques, intending to provide the research community an overview of the results obtained looking to the next future. Furthermore, we describe in detail the most used databases to address the problem of facial expressions and emotions, highlighting the results obtained by the various authors. The different techniques used are compared, and some conclusions are drawn concerning the best recognition rates achieved.

Emmanuel Levinas: Um estudo sobre a ética da alteridade

2020 ◽  
Author(s):  
Abimael Francisco do Nascimento
Keyword(s):  
Emmanuel Levinas ◽  
Transcendental Philosophy ◽  
The Other ◽  
New Thought ◽  
Philosophical Criticism ◽  
The Face ◽  
The Subject ◽  
Theoretical Foundations ◽  
First Philosophy

The general objective of this study is to analyze the postulate of the ethics of otherness as the first philosophy, presented by Emmanuel Levinas. It is a proposal that runs through Levinas' thinking from his theoretical foundations, to his philosophical criticism. Levinas' thought presents itself as a new thought, as a critique of ontology and transcendental philosophy. For him, the concern with knowledge and with being made the other to be forgotten, placing the other in totality. Levinas proposes the ethics of otherness as sensitivity to the other. The subject says here I am, making myself responsible for the other in an infinite way, in a transcendence without return to myself, becoming hostage to the other, as an irrefutable responsibility. The idea of the infinite, present in the face of the other, points to a responsibility whoever more assumes himself, the more one is responsible, until the substitution by other.

СОЦИАЛЬНАЯ КОНФЛИКТОЛОГИЯ: ТЕОРЕТИКО-ИСТОРИЧЕСКИЙ АСПЕКТ

2020 ◽  
Vol 15 (2) ◽  
pp. 68
Author(s):  
А. Н. Сухов
Keyword(s):  
Theory And Practice ◽  
Important Task ◽  
Social Conflicts ◽  
Psychological Approach ◽  
Structure Dynamics ◽  
History Of ◽  
The Subject ◽  
First Time

This given article reveals the topicality not only of destructive, but also of constructive, as well as hybrid conflicts. Practically it has been done for the first time. It also describes the history of the formation of both foreign and domestic social conflictology. At the same time, the chronology of the development of the latter is restored and presented objectively, in full, taking into account the contribution of those researchers who actually stood at its origins. The article deals with the essence of the socio-psychological approach to understanding conflicts. The subject of social conflictology includes the regularities of their occurrence and manifestation at various levels, spheres and conditions, including normal, complicated and extreme ones. Social conflictology includes the theory and practice of diagnosing, resolving, and resolving social conflicts. It analyzes the difficulties that occur in defining the concept, structure, dynamics, and classification of social conflicts. Therefore, it is no accident that the most important task is to create a full-fledged theory of social conflicts. Without this, it is impossible to talk about effective settlement and resolution of social conflicts. Social conflictology is an integral part of conflictology. There is still a lot of work to be done, both in theory and in application, for its complete design. At present, there is an urgent need to develop conflict-related competence not only of professionals, but also for various groups of the population.

scholarly journals Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3046
Author(s):  
Shervin Minaee ◽  
Mehdi Minaei ◽  
Amirali Abdolrashidi
Keyword(s):  
Deep Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Visualization Technique ◽  
Convolutional Network ◽  
The Past ◽  
Multiple Datasets ◽  
The Face ◽  
Traditional Approaches

Facial expression recognition has been an active area of research over the past few decades, and it is still challenging due to the high intra-class variation. Traditional approaches for this problem rely on hand-crafted features such as SIFT, HOG, and LBP, followed by a classifier trained on a database of images or videos. Most of these works perform reasonably well on datasets of images captured in a controlled condition but fail to perform as well on more challenging datasets with more image variation and partial faces. In recent years, several works proposed an end-to-end framework for facial expression recognition using deep learning models. Despite the better performance of these works, there are still much room for improvement. In this work, we propose a deep learning approach based on attentional convolutional network that is able to focus on important parts of the face and achieves significant improvement over previous models on multiple datasets, including FER-2013, CK+, FERG, and JAFFE. We also use a visualization technique that is able to find important facial regions to detect different emotions based on the classifier’s output. Through experimental results, we show that different emotions are sensitive to different parts of the face.

scholarly journals The Law Challenged and the Critique of Identity with Emmanuel Levinas

2021 ◽  
Author(s):  
Susan Petrilli
Keyword(s):  
Human Rights ◽  
Emmanuel Levinas ◽  
Object Relation ◽  
Legal Order ◽  
The Other ◽  
Ethical Orientation ◽  
New Humanism ◽  
Present Essay ◽  
The Face ◽  
The Subject

AbstractIdentity as traditionally conceived in mainstream Western thought is focused on theory, representation, knowledge, subjectivity and is centrally important in the works of Emmanuel Levinas. His critique of Western culture and corresponding notion of identity at its foundations typically raises the question of the other. Alterity in Levinas indicates existence of something on its own account, in itself independently of the subject’s will or consciousness. The objectivity of alterity tells of the impossible evasion of signs from their destiny, which is the other. The implications involved in reading the signs of the other have contributed to reorienting semiotics in the direction of semioethics. In Levinas, the I-other relation is not reducible to abstract cognitive terms, to intellectual synthesis, to the subject-object relation, but rather tells of involvement among singularities whose distinctive feature is alterity, absolute alterity. Humanism of the other is a pivotal concept in Levinas overturning the sense of Western reason. It asserts human duties over human rights. Humanism of alterity privileges encounter with the other, responsibility for the other, over tendencies of the centripetal and egocentric orders that instead exclude the other. Responsibility allows for neither rest nor peace. The “properly human” is given in the capacity for absolute otherness, unlimited responsibility, dialogical intercorporeity among differences non-indifferent to each other, it tells of the condition of vulnerability before the other, exposition to the other. The State and its laws limit responsibility for the other. Levinas signals an essential contradiction between the primordial ethical orientation and the legal order. Justice involves comparing incomparables, comparison among singularities outside identity. Consequently, justice places limitations on responsibility, on unlimited responsibility which at the same time it presupposes as its very condition of possibility. The present essay is structured around the following themes: (1) Premiss; (2) Justice, uniqueness, and love; (3) Sign and language; (4) Dialogue and alterity; (5) Semiotic materiality; (6) Globalization and the trap of identity; (7) Human rights and rights of the other: for a new humanism; (8) Ethics; (9) The World; (10) Outside the subject; (11) Responsibility and Substitution; (12) The face; (13) Fear of the other; (14) Alterity and justice; (15) Justice and proximity; (16) Literary writing; (17) Unjust justice; (18) Caring for the other.

scholarly journals Facial Expression Recognition Based on Multi-Features Cooperative Deep Convolutional Network

2021 ◽  
Vol 11 (4) ◽  
pp. 1428
Author(s):  
Haopeng Wu ◽  
Zhiying Lu ◽  
Jianfeng Zhang ◽  
Xin Li ◽  
Mingyue Zhao ◽  
...  
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Video Data ◽  
Expression Recognition ◽  
Convolutional Network ◽  
Facial Movements ◽  
The Face ◽  
Deep Convolutional Network ◽  
Selection Of

This paper addresses the problem of Facial Expression Recognition (FER), focusing on unobvious facial movements. Traditional methods often cause overfitting problems or incomplete information due to insufficient data and manual selection of features. Instead, our proposed network, which is called the Multi-features Cooperative Deep Convolutional Network (MC-DCN), maintains focus on the overall feature of the face and the trend of key parts. The processing of video data is the first stage. The method of ensemble of regression trees (ERT) is used to obtain the overall contour of the face. Then, the attention model is used to pick up the parts of face that are more susceptible to expressions. Under the combined effect of these two methods, the image which can be called a local feature map is obtained. After that, the video data are sent to MC-DCN, containing parallel sub-networks. While the overall spatiotemporal characteristics of facial expressions are obtained through the sequence of images, the selection of keys parts can better learn the changes in facial expressions brought about by subtle facial movements. By combining local features and global features, the proposed method can acquire more information, leading to better performance. The experimental results show that MC-DCN can achieve recognition rates of 95%, 78.6% and 78.3% on the three datasets SAVEE, MMI, and edited GEMEP, respectively.

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