An emotion plays an important role in overall development of student. There are various types of emotions students can face while learning. Education is one major sector which has undergone the in?uence of innovations in ICT (Information and Communication Technology). ICT provides platforms for E-learning. Like traditional learning, students can experience variety of emotions in E-learning. These emotions are anger, happiness, surprise, confusion, contempt, curiosity, etc. The analysis of these emotions will helpful in improving ICT enabled resources.
Emotion is a mental state which involves actions, thoughts and feelings.
Human uses the emotions for expressing feelings. In 1872, Charles Darwin’s book “The expression of emotions in human and animals” was published. This book gives information about various emotions. Humans can understand each other with the help of emotions. Humans can see the emotions by mood. Emotion is more powerful tool to express the feelings. Humans interact with each other directly or indirectly. While interacting with each other, emotions play an important role.
Information and Communication Technology (ICT) enables self-paced learning through various tools.
Student can experience variety of emotions during ICT based education. These emotions play an important role in students’ performance. Students’ performance is measured with the help of assessment techniques. Student assessment could be a vital facet of the teaching and learning method. Student assessment allows instructors to measure the e?ectiveness of their teaching by linking student performance to speci?c learning objectives. As a result, academicians are able to commit e?ective teaching choices and revise ine?ective ones in their pedagogy.
The major problem found with use of ICT is technophobia. While more and more teaching is given through different technological equipment, more troubles are encountered by the people, because of the negative feelings they have towards them. Frustration and anxiety are known to be part of the computer user’s life; almost all of the users at some point feel themselves frustrated. Frustration causes people to withdraw from the frustrating situation and make them not to go through the frustrating situation again.
There are several definitions of technophobia, however the foremost normally cited definition is that the one projected by Jay (1981) who outlined it as:
Use of technology in education plays important role. ICT provides tools for using information for thinking and expression.
There are some barriers to ICT based E-Learning which are lack of student motivation, lack of customization to student’s interest, lack of personal community and connection, lack of quality assessment and feedback, domestic distractions and program cost.
Emotions are responses to important internal and external events. Facial expressions and body language are the key features in interaction. In a book written by Charles Darwin, He published globally shared facial expressions that play an important role in non-verbal communication [3]. Apparently humans, but also animals, develop similar muscular movements belonging to a certain mental state, despite their place of birth, race, and education.
In communication major part of the message is described by the emotions. Recognition of these emotions is helpful in understanding the meaning of the messages.
Modern psychology defines six basic facial expressions: Happiness, Sadness, Surprise, Fear, Disgust, and Anger as universal emotions [2].
Facial muscles movements help to identify human emotions. Basic facial expressions are hair, mouth, nose & eyes.
Happiness is most common expression by human. The related other emotions are cheerfulness, pride, relief, hope, pleasure, and thrill.
Sadness is opposite of happiness. Other related emotions are suffering, hurt, despair and hopelessness.
This emotion is seen when unexpected things happens. Other related emotions of surprise are amazement, astonishment.
Fear represents danger. It may be due to danger of physical or psychological damage. Other emotions related to fear are horror, nervousness, panic, worry and dread.
Disgust represents dislike. Human could feel disgust from any style, smell, sound or tough.
Anger is one of the most dangerous emotions. This feeling is also harmful therefore, humans are trying to avoid this emotion. Other emotions of anger are irritation, annoyance, frustration, hate and dislike.
Recent works with deep learning technique has been performed with completely different sorts of input of human behavior like audio-visual inputs, facial expressions, body gestures, EEG signal and connected brainwaves.
Human can find emotions without any significant delay and effort but recognizing facial expression by machine is a big challenge. Human can find emotions with the help of facial expressions, speech, conversation, body temperature and sensors.
Some of the important facial expression recognition techniques are:
This paper was based on noise and rotation invariant facial expression recognition based on Statistical movement. Statistical movement is also called Zernike moments [3]. The extracted feature forms Zernike moments are given as input to Na?ve Bayesian classifier for emotion recognition.
In this paper, facial expressions are determined using localization of points called Action Unit (AU’s) without labeling them [4]. Face is recognized by using the skin of the extracted image. By using mapping technique extracted eyes and mouth are mapped together. Skin and non-skin pixels are separated to separate face from the background by using Haar-Cascaded method. It works on Illumination on image plays important role.
This paper proposed E-learning based emotion recognition system [6].SVM (Support Vector Machine) classifier based Ad boost algorithm used to locate human face. Ad boost algorithm compares the classifier by extracting features with week classifier to strong classifier. This is iterative weight updating process. It presents application of face emotion recognition with of E-learning system.
In this paper, emotion detection of members watching TV program is proposed [7]. Face expression recognition are used to identify specific TV viewer and recognize their internal emotional state. Ada-LDA method based recognition. Per second over 15 frames can operated. It presents application of face emotion recognition with of E-learning system.
Active Infra-Red (IR) illumination is used to find out facial features [8]. Source Vector (SV) is used. It gives a vector collection which shows motion and deformation due to emotion representation. Emotions are classified according to the estimated similarity between the source vector and execution motion vector and highest degree of similarity could be identified as detected emotion. It has real time performance with high recognition rate.
Extensive efforts have been made over the past two decades in academia, industry, and government to discover more robust methods of assessing truthfulness, deception, and credibility during human interactions. Efforts have been made to catch human expressions of anyone. Emotions are due to any activity in brain and it is known through face, as face has maximum sense organs. Hence human facial activity is considered. The objective of this research paper is to give brief introduction towards techniques, application and challenges of automatic emotion recognition system.
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