Facial Expressions Recognition Using Web Camera

Data Mining Through Facial Expressions

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Inspiration

Human gesture is the thing which plays a very interesting role in general life application. It can be easily recognize using image processing. Let us consider an example of driver’s gesture who is currently driving the vehicle and it will be quiet useful in case of alerting him when he is in sleepy mood. We can identify the human gesture by observing the movements of eyes, nose, brows, cheeks which may vary with time. The proposed system is introduced for recognizing the expressions by focusing on human face. There were two implementation the approach is based on that is face detection classifier and finding and matching of simple token.

What it does

Performance of employees’ working in MNCs can be monitored using the proposed system. The system will let the Company’s HR to monitor the particular employee’s mood and on that basis able to decides its performance. The proposed system can be very useful in generating pie charts, bar graph, etc upon employee analysis result. Mood will obviously affect the work in positive as well as negative manner and changes in work can be specified with the help of employee analysis result. Using the proposed system the user and admin system for control can also be developed.

Our application will not only detect the users’ mood but also provide the relevant data from database for boosting the mood of user. For example, the system will automatically fetch the songs or jokes from database and send it on the users’ window terminal if user is in sad mood. And also system will able to provide some links to web pages of motivational speech. The data provide by system will boost the mood which make the user to work efficiently and leads to enhancement in performance.

How we built it

Challenges we ran into

The human face plays a prodigious role in the automatic recognition of emotions in the field of human emotion identification and human-computer interaction for real applications such as driver status monitoring, personalized learning, health monitoring, etc. . However, they are not considered dynamic characteristics independent of the subject, so they are not robust enough for the task of recognizing real life with the variation of the subject (human face), the movement of the head and the change of illumination. In this article, we tried to design an automated framework for detecting emotions using facial expression. For human-computer interaction, facial expression is a platform for non-verbal communication. Emotions are actually changing events that are evoked as a result of the driving force. Thus, in the application of real life.

Accomplishments that we're proud of

What we learned

   In the field of image processing, it is very interesting to recognize the human gesture for the applications of life in general. For example, it is very useful to observe the gesture of a driver when the person is driving and warning the person when he is sleepy. We can identify human gestures by observing the different movements of eyes, mouth, nose and hands. In this proposed system focuses on the human face to recognize the expression. Many techniques are available to recognize the face. This system presents a simple architecture for recognizing human facial expression. The approach is based on a classifier for detecting faces and searching and matching simple symbols. This approach can be very easily adapted to the system in real time. The system briefly describes the image capture patterns from the webcam, face detection, image processing to recognize gestures and some results,In the field of image processing, it is very interesting to recognize the human gesture for the applications of life in general. For example, it is very useful to observe the gesture of a driver when the person is driving and warning the person when he is sleepy. We can identify human gestures by observing the different movements of eyes, mouth, nose and hands. In this proposed system focuses on the human face to recognize the expression. Many techniques are available to recognize the face. This system presents a simple architecture for recognizing human facial expression. The approach is based on a classifier for detecting faces and searching and matching simple symbols. This approach can be very easily adapted to the system in real time. The system briefly describes the image capture patterns from the webcam, face detection, image processing to recognize gestures and some results.

What's next for Facial Expressions Recognition Using Web Camera

There is one more approach we have adapted i.e. chatbot which is built using artificial intelligence. Using chatting application system let the user to chat with bot and this leads to identifying the users’ mood on the basis of text or speech using text processing. Considering the both approaches the system will be able to provide jokes, songs and links to webpages by recognizing the users’ response. .

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