Detection of face emotions on live web camera conversation

This project focuses on detecting human face emotions on live web camera. During a live stream, system will identify  the emotion on the face of the person , if  a person is happy, sad, disgusted, angry, surprised or neutral. System will classify the emotion and it will be displayed with l

Project Title

Detection of face emotions on live web camera conversation

Project Area of Specialization

Artificial Intelligence

Project Summary

This project focuses on detecting human face emotions on live web camera. During a live stream, system will identify  the emotion on the face of the person , if  a person is happy, sad, disgusted, angry, surprised or neutral. System will classify the emotion and it will be displayed with live feed of video. System will also find the degree of emotion on human face in terms of “normal”, “very” and “extremely”.

By evaluating the emotional state, there is an attempt to overcome the barrier between man and non-emotional machine.” This software can be applied in various fields of life and activities, and evaluating emotions concerning statement on online learning, for example, is necessary to improve qualities or collecting statistics of personal impressions for researchers. For the project, “Res-Net Cifar 10” data model will be used to recognize emotions. Since, face features of people of different origins are distinct to some extent, aim is to take this model and work by training   it for our own data in future.

This software can be applied in various fields of life and activities, and evaluating emotions concerning statement on online learning, for example, is necessary to improve qualities or collecting statistics of personal impressions for researchers.

OpenCV and CNN methods will be used to detect object and realize emotion on the face.

Project Objectives

1. Object classification to identify the human face on live feed.
2. Emotion identification on live video feed.
3. Estimation intensity estimation.

Project Implementation Method

1. This project focuses on detecting face emotions on live web camera conversation by coding on python, using open source library of Anaconda to join and
2. Utilize OpenCV and CNN methods to detect object and realize emotion on the face, and PyCharm is used to show the result.

Benefits of the Project

This software  can be used in various fields of life and activities, and evaluating emotions concerning statement on online learning, for example, is necessary to improve qualities or collecting statistics of personal impressions for researchers.

In the future, plan is to expand this project to detect multiple emotions on human faces. This system will be very helpful to the multinational company for their security systems and to enhance their business and at public sector e.g. Airport security, police station criminal’ investigation concern’s. Additionally, it is possible to develop these projects in the form of mobile applications. In today's mobile world, such applications would be downloaded and used on a large scale.

Technical Details of Final Deliverable

• Object detection system.
  • In first step, object detection system will be designed as prototype. This system will have the ability to detect the human face in a live video feed.
• Training of  data model for emotion detection.
  • This deliverable will be able to output a  trained model which could be used to classify the emotions.
• Emotion Intensity Checker
  • This component will check the intensity of the emotion on a  human face.
• Software system that could classify human emotions with intensities.
  • This will be an integrated system with all above mentioned features in it.
• Project documentation
  • User manual will also be provided to get information about software usage.

Final Deliverable of the Project

Software System

Type of Industry

IT , Medical , Security

Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Industry, Innovation and Infrastructure, Partnerships to achieve the Goal

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com