scholarly journals Emotion Recognition - the need for a complete analysis of the phenomenon of expression formation

2018 ◽  
Vol 26 ◽  
pp. 00013
Author(s):  
Katarzyna Bobkowska ◽  
Marek Przyborski ◽  
Dariusz Skorupka
Keyword(s):  
High Speed ◽  
Pair Correlation ◽  
Correlation Coefficients ◽  
Complete Analysis ◽  
Human Face ◽  
Facial Image ◽  
Maximum Change ◽  
Complex Emotions ◽  
The Face ◽  
Micro Expression

This article shows how complex emotions are. This has been proven by the analysis of the changes that occur on the face. The authors present the problem of image analysis for the purpose of identifying emotions. In addition, they point out the importance of recording the phenomenon of the development of emotions on the human face with the use of high-speed cameras, which allows the detection of micro expression. The work that was prepared for this article was based on analyzing the parallax pair correlation coefficients for specific faces. In the article authors proposed to divide the facial image into 8 characteristic segments. With this approach, it was confirmed that at different moments of emotion the pace of expression and the maximum change characteristic of a particular emotion, for each part of the face is different.

Improved Face Recognition With Fractal-Based Texture Analysis

2021 ◽  
Vol 11 (3) ◽  
pp. 41-53
Author(s):  
Rajalaxmi Padhy ◽  
Aishwarya Dash ◽  
Sanjit Kumar Dash ◽  
Jibitesh Mishra
Keyword(s):  
The Self ◽  
Human Vision ◽  
Svm Classifier ◽  
Human Face ◽  
Facial Image ◽  
Processing Stage ◽  
Proposed Model ◽  
The Face ◽  
System Maps ◽  
Self Similar

Fractals are useful to uniquely represent texture in the human face, which serves as an equivalent of human vision. FaceNet, calculating face descriptors of a person, has been observed to perform with setbacks when several factors of occlusion are present. This paper proposes a new methodology that exploits the self-similar patterns in a person's face to highlight and enhance regions of high texture in a facial image. The system maps the original image into a representation in the pre-processing stage of computer vision. This representation when fed as an input to the FaceNet CNN optimizes the face embedding generated. An SVM classifier separates the hard positive examples from the hard negative examples during classification. The model is trained using YouTube Faces DB as primary dataset and for validation; a custom dataset is designed to verify a person's identity despite the presence of secondary factors such as expressions and forgery. The proposed model attained an overall accuracy of 96.73% with the YouTube Faces DB, and a notable reduction in the false positive rates is observed.

scholarly journals FACE RECOGNITION THROUGH CASCADE CLASSIFIER USING EIGENFACES ALGORITHMS.

2020 ◽  
Vol 9 (6) ◽  
pp. 39-47
Keyword(s):  
Face Recognition ◽  
Dimensional Space ◽  
Principal Component ◽  
Face Image ◽  
Human Face ◽  
Cascade Classifier ◽  
Facial Image ◽  
Human Face Recognition ◽  
Cascade Classifiers ◽  
The Face

The easiest way to distinguish each person's identity is through the face. Face recognition is included as an inevitable pre-processing step for face recognition. Face recognition itself has to face difficulties and challenges because sometimes some form of issue is quite different from human face recognition. There are two stages used for the human face recognition process, i.e. face detection, where this process is very fast in humans. In the first phase, the person stored the face image in the database from a different angle. The person's face image storage with the help of Eigenvector value depended on components - face coordinates, face index, face angles, eyes, nose, lips, and mouth within certain distances and positions with each other. There are two types of methods that are popular in currently developed face recognition patterns, the Cascade Classifier method and the Eigenface Algorithm. Facial image recognition The Eigenface method is based on the lack of dimensional space of the face, using principal component analysis for facial features. The main purpose of the use of cascade classifiers on facial recognition using the Eigenface Algorithm was made by finding the eigenvectors corresponding to the largest eigenvalues of the facial image

scholarly journals Accuracy of the interpersonal perception by human face in a communicative situation

2019 ◽  
Vol 12 (2) ◽  
pp. 8-15
Author(s):  
K.I. Ananyeva ◽  
N.O. Tovuu
Keyword(s):  
Personal Characteristics ◽  
Morphological Type ◽  
Interpersonal Perception ◽  
Human Face ◽  
Facial Image ◽  
Joint Decision ◽  
Two Samples ◽  
Region Of Residence ◽  
The Face ◽  
Study Participants

We studied the adequacy of the assessment of personal characteristics in the perception of people of different races (Caucasoid and Mongoloid) in situations of individual and joint decision making. The study involved two samples of subjects, residents of Moscow and Kyzyl (Republic of Tyva). The adequacy of assessing the personal characteristics of the sitters was analyzed using the values received from the scales of the “Personal Differential” questionnaire. The grouping variables were the region of residence of study participants and the morphological type of the face of the sitter. It is shown that the adequacy of assessing personality based on face perception is selective, and the possibility of discussing one’s own impressions with a partner can be both a resource and a hindrance to the adequacy of judgments about a personality based on a facial image.

Conventions and temporal differences in painted faces: A study of posture and color distribution

2020 ◽  
Vol 2020 (11) ◽  
pp. 267-1-267-8
Author(s):  
Mitchell J.P. van Zuijlen ◽  
Sylvia C. Pont ◽  
Maarten W.A. Wijntjes
Keyword(s):  
Scientific Community ◽  
Human Face ◽  
Art Galleries ◽  
Art Collections ◽  
Color Distribution ◽  
Scientific Domain ◽  
The Face ◽  
And Gender ◽  
Changes Over Time ◽  
Over Time

The human face is a popular motif in art and depictions of faces can be found throughout history in nearly every culture. Artists have mastered the depiction of faces after employing careful experimentation using the relatively limited means of paints and oils. Many of the results of these experimentations are now available to the scientific domain due to the digitization of large art collections. In this paper we study the depiction of the face throughout history. We used an automated facial detection network to detect a set of 11,659 faces in 15,534 predominately western artworks, from 6 international, digitized art galleries. We analyzed the pose and color of these faces and related those to changes over time and gender differences. We find a number of previously known conventions, such as the convention of depicting the left cheek for females and vice versa for males, as well as unknown conventions, such as the convention of females to be depicted looking slightly down. Our set of faces will be released to the scientific community for further study.

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

Micro-Expression Recognition using 3D - CNN

2020 ◽  
pp. 5-13
Author(s):  
Vishal Dubey ◽  
◽  
◽  
◽  
Bhavya Takkar ◽  
...  
Keyword(s):  
Emotional Response ◽  
High Speed ◽  
Actual State ◽  
Time Interval ◽  
Short Time Interval ◽  
Expression Recognition ◽  
Specific Emotion ◽  
3D Cnn ◽  
Short Time ◽  
Micro Expression

Micro-expression comes under nonverbal communication, and for a matter of fact, it appears for minute fractions of a second. One cannot control micro-expression as it tells about our actual state emotionally, even if we try to hide or conceal our genuine emotions. As we know that micro-expressions are very rapid due to which it becomes challenging for any human being to detect it with bare eyes. This subtle-expression is spontaneous, and involuntary gives the emotional response. It happens when a person wants to conceal the specific emotion, but the brain is reacting appropriately to what that person is feeling then. Due to which the person displays their true feelings very briefly and later tries to make a false emotional response. Human emotions tend to last about 0.5 - 4.0 seconds, whereas micro-expression can last less than 1/2 of a second. On comparing micro-expression with regular facial expressions, it is found that for micro-expression, it is complicated to hide responses of a particular situation. Micro-expressions cannot be controlled because of the short time interval, but with a high-speed camera, we can capture one's expressions and replay them at a slow speed. Over the last ten years, researchers from all over the globe are researching automatic micro-expression recognition in the fields of computer science, security, psychology, and many more. The objective of this paper is to provide insight regarding micro-expression analysis using 3D CNN. A lot of datasets of micro-expression have been released in the last decade, we have performed this experiment on SMIC micro-expression dataset and compared the results after applying two different activation functions.

Within-Subject Correlation Between Salivary IgA and Measures of Training Load in Elite Football Players

2019 ◽  
Vol 14 (6) ◽  
pp. 847-849 ◽  
Author(s):  
Pedro Figueiredo ◽  
George P. Nassis ◽  
João Brito
Keyword(s):  
High Speed ◽  
Perceived Exertion ◽  
Immunoglobulin A ◽  
Correlation Coefficients ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Football Players ◽  
Positioning Systems ◽  
External Training ◽  
Salivary Secretory Immunoglobulin A

Purpose: To quantify the association between salivary secretory immunoglobulin A (sIgA) and training load in elite football players. Methods: Data were obtained on 4 consecutive days during the preparation camp for the Rio 2016 Olympic Games. Saliva samples of 18 elite male football players were collected prior to breakfast. The session rating of perceived exertion (s-RPE) and external training-load metrics from global positioning systems (GPS) were recorded. Within-subject correlation coefficients between training load and sIgA concentration, and magnitude of relationships, were calculated. Results: sIgA presented moderate to large negative correlations with s-RPE (r = −.39), total distance covered (r = −.55), accelerations (r = −.52), and decelerations (r = −.48). Trivial to small associations were detected between sIgA and distance covered per minute (r = .01), high-speed distance (r = −.23), and number of sprints (r = −.18). sIgA displayed a likely moderate decrease from day 1 to day 2 (d = −0.7) but increased on day 3 (d = 0.6). The training-load variables had moderate to very large rises from day 1 to day 2 (d = 0.7 to 3.2) but lowered from day 2 to day 3 (d = −5.0 to −0.4), except for distance per minute (d = 0.8) and sprints (unclear). On day 3, all training-load variables had small to large increments compared with day 1 (d = 0.4 to 1.5), except for accelerations (d = −0.8) and decelerations (unclear). Conclusions: In elite football, sIgA might be more responsive to training volume than to intensity. External load such as GPS-derived variables presented stronger association with sIgA than with s-RPE. sIgA can be used as an additional objective tool in monitoring football players.

scholarly journals Response to Melissa Raphael

2016 ◽  
Vol 6 (2) ◽  
pp. 23-25
Author(s):  
Ruth Illman
Keyword(s):  
Digital Media ◽  
Image Of God ◽  
Human Face ◽  
Human Beings ◽  
Jewish Art ◽  
Contemporary Issue ◽  
The Face ◽  
The Creation ◽  
The Image Of God ◽  
Ethical Demand

A response to Melissa Raphael’s article ‘The creation of beauty by its destruction: the idoloclastic aesthetic in modern and contemporary Jewish art’. Key themes discussed include the notion of human beings as created in the image of God, Levinas’s understanding of the face and its ethical demand as well as the contemporary issue of the commodification of the human face in digital media.

scholarly journals ANALYSIS OF EXPERIENCE IN THE APPLICATION OF MISSILE LAUNCH DETECTION SYSTEMS

2021 ◽  
pp. 118-129
Author(s):  
A. Pinchuk ◽  
M. Garbuz ◽  
P. Zeleny ◽  
D. Harnets ◽  
D. Ivanov
Keyword(s):  
High Speed ◽  
Armed Forces ◽  
The United States ◽  
Armed Conflicts ◽  
Desert Storm ◽  
Detection Systems ◽  
The Face ◽  
Protected Object ◽  
Conducting Research ◽  
The Impact

Analysis of combat losses of aircraft in local armed conflicts in recent decades shows that most cases of aircraft hits are related to the impact of guided surface-to-air and air-to-air missiles equipped with homing warheads. The use of modern guided missiles equipped with homing warheads is one of the main threats to aircraft of various types. This is due to the fact that modern guided missiles are characterized by high speed, maneuverability, accuracy of aiming and difficulty of detection. Solving the problem of protecting aircraft from guided missiles consists of several stages: detection of missile launch; confirmation that the detected missile is heading directly toward the protected object; missile identification and decision-making on the most effective countermeasure system employment. At present, there are no missile launch detection systems that guarantee a 100% probability of threat detection, but an analysis of aviation combat losses in local armed conflicts in recent decades convincingly shows that the number of combat losses of aircraft equipped with such systems is much lower than those in which missile launch detection is carried out visually. For example, most of the Soviet Union's losses during the war in Afghanistan and the United States‟ losses during Operation “Desert Storm” in Iraq were related to the use of portable anti-aircraft missile systems, which missiles were equipped with infrared homing warheads. Realizing the scale of the threat posed by such missiles, most of the world's leading countries have significantly increased the expenses on development new or improvement existing countermeasures. As a result, the aggregate losses of coalition forces in Iraq, Afghanistan and Syria since 2001 clearly suggest that these costs have paid off, with losses from the use of portable anti-aircraft missile systems significantly reduced, while the total number of combat sorties increased. Therefore, in the face of all the challenges and threats posed to Ukraine due to the aggressive actions of the Russian Federation, conducting research in the interests of aviation of the Armed Forces of Ukraine to improve the effectiveness of missile detection systems for ensuring timely detection of threats, warning of aircraft crew and activation in the automatic mode the means of countermeasures is as relevant as ever.

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