It is a technique used to read the emotions on a human face by using image processing. The program can recognize emotions, such as anger, sadness, fear, joy, disgust, surprise, trust, and so on.It can be used by company to detect the Facial emotion of employee or, Facial Emotion Detection in Interviews to hire candidates, digital advertising, etc..
In the film industry, market research is generally qualitative and the data that is collated from surveys, reviews, and post-screening reactions is usually done manually. Some film companies, however, are taking advantage of emotion detection software and are using it to determine how moviegoers are enjoying their films. They do this by letting the software capture people’s faces and track facial behavior using infrared cameras during movie screenings.
All this is done in real-time which generates reliable data, helping movie production companies get a more accurate picture of audience responses. Ultimately, what these companies get out of this, is greater insight into what provokes an emotion.
Many of the most successful marketing campaigns and initiatives are focused on eliciting emotions. This is how companies or brands connect with their audiences. Digital marketing professionals are leveraging the power of emotion detection to understand the emotions of their potential customers to improve customer experiences and to create a lasting bond.
To begin with, analyzing various facial expressions and behavior can help to figure out the emotional state of a customer. This, subsequently, helps to recommend products that will satisfy the customers’ requirements and expectations. When your content or brand can connect with prospective buyers emotionally, it will drive them to make a purchase. Hence, it will boost your business.
Furthermore, being able to adjust marketing dynamically, based on the real-time responses of your audience, will empower marketers to provide the right message at the right time to the right person.
It is used to detect expression of employee about thier work, wheather they feel stress, or enjoy the works, wheather they need break, or not fit for job.
Companies are not only using emotion-detection technology for consumer-facing applications. Some employ this technology to screen prospective candidates based on factors like body language and mood. In doing so, a company is able to find the person whose personality and characteristics are best suited to the job.
By analyzing body language and facial expressions, the algorithm can predict how the candidate might react or behave in certain situations. It also can pick up whether or not a candidate is being truthful, as well as their general confidence levels based on how emotions change during responses. Ultimately disposing of prolonged hiring processes.
Healthcare is another industry that could benefit from this technology. Because detection software is AI-powered, it could potentially help determine when patients need medicine or to help doctors prioritize who to see.
In the manufacturers’ quest to build smart cars, it makes sense for them to use AI to assist them in understanding human emotions. Emotion detection software in cars can enhance the overall user experience while also improving car safety. If a car is smart enough to detect the emotional state of a driver, it can help prevent accidents by sending signals to the driver to stop the car or apply breaks. It can even go as far as to suggest music based on the driver’s mood or change the temperature for the better.
Dataset is taken from kaggle.
https://www.kaggle.com/jonathanoheix/face-expression-recognition-dataset
(Image is already pre-processed)
The model can identify 7 kinds of emotion.
1.Sad
2.Angry
3.Disgust
4.Fear
5.Happy
6.Neutral
7.Surprise
python
Anaconda
Jupyter Notebook
Keras
tensorflow
numpy
matplotlib
cv2
opencv
pickle
