Facial Emotion Detection Using AI: Use Cases

Sentiment Analysis is currently widely employed by different businesses to gauge consumer disposition towards their brand or product in the digital world. However, in the offline world, users are also interacting with the brands and products in retail stores, showrooms, etc., and also alternatives to measure users' reactions automatically under such settings has turned into a challenging task. Emotion detection from facial expressions utilizing AI can be a viable alternative to automatically measure consumers' involvement with their content and brands.

In this post, we will discuss how this type of technology can be used to fix a variety of real-world use-cases effectively.

1. Making Cars Safer and Personalized

Automobile manufacturers around the world are increasingly focusing on making cars more personal and safe for us to push. In their pursuit to construct more smart car attributes, it seems sensible for makers to use AI to assist them understand human emotions. Employing facial emotion detection smart automobiles can alert the driver if he's feeling drowsy.

The US Department of Transportation claims that driving-related mistakes cause around 95% of fatal road accidents. Facial emotion discovery can discover subtle changes in facial micro-expressions that precedes nausea and send personalized alerts to the driver asking him to stop for a coffee break, change the music, or modify the temperature.

2. Facial Emotion Detection in Interviews

A candidate-interviewer interaction is vulnerable to many types of judgment and subjectivity. Such subjectivity makes it hard to determine if a candidate's character is a good match for your job. Discovering what a candidate is attempting to say is from our hands due to the multiple layers of speech interpretation, cognitive biases, and context that lie in between. That is where AI comes in, which may measure a candidate's facial expressions to capture their moods and further assess their character traits.

Notably, Unilever is already beginning to integrate this technology in their recruitment procedure. With this technology, a professional will have the ability to understand, say, the total confidence level of an interviewee and make a decision about whether or not this candidate will have the ability to perform well at a client-facing project. Similarly, it is going to be possible to discover if the candidate is actually responding to each of the questions by measuring the change in emotions during his responses and correlating it the huge quantity of knowledge available in this area.

Employee morale may also be perceived using this technology by recording and holding interactions at work. As an HR tool, it may help not just in devising recruiting plans but also in designing HR policies which bring about the very best performance from workers.

3. Assessing for Video Games

Video games are designed keeping in mind a specific target audience. Every video game intends to evoke a particular behavior and pair of emotions from your consumers. During the testing period, users are requested to play the game for a given period and their opinions is integrated to generate the final product. Using facial emotion detection can aid in understanding which emotions a user is moving through in real time as he's playing without assessing the complete movie manually.

Such merchandise comments could be taken by analyzing a live feed of the consumer and discovering his face emotions. While feelings of frustration and anger are generally experienced in complex video games, using facial emotion detection will help understand which feelings are experienced at certain points in the match. It is also possible that a few unexpected or undesirable emotions are observed through the sport. AI testing services helps you in maintaining your website effectively. 

Taking feedback from the consumer has undergone the sport could be ineffective. This is only because it can frequently be hard to place an encounter into words. Moreover, users may be unable to remember what exactly they went through emotionally across different parts of the game. Cosmetic Emotion detection is a practical way of going beyond the written or spoken feedback and enjoying what the user is experiencing. When feedback is taken in this format, it becomes genuinely non-intrusive when it comes to user experience. At precisely the exact same time, such opinions is more reliable than other forms.

4. Market Research

Traditionally, market research businesses have employed verbal techniques such as surveys to discover the consumers wants and needs. However, such methods assume that customers can formulate their tastes verbally and the stated preferences correspond to future activities, which may not always be appropriate.

Another popular strategy in the market research industry is to employ behavioral procedures that observe a consumer's response whilst interacting with a new or product. Such methods are considered more goal than verbal methods. 

Behavioral methods utilize video feeds of consumers interacting with the product, which can be subsequently analyzed manually to observe their reactions and emotions. However, such techniques can quickly become quite labour intensive as the sample size increase. Facial emotion recognition can come to the rescue by allowing market research companies to measure moment-by-moment facial expressions of emotions (facial coding) mechanically and aggregate the results.