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The Ultimate Guide to Emotion Recognition from Facial Expressions using Python
Build a Face Emotion Recognition (FER) Algorithm that works on both, Images and Videos
Emotion is one of the very few words in the English language that do not have a concrete definition and it is understandable. It is abstract. Yet, almost every decision we have ever made in our lives is driven by emotion. Marketing research has proven that predicting sentiments correctly can be a huge source of growth for businesses and that’s what we will be working on today — Reading Emotions. In the world of data and machine learning, this concept falls under the umbrella of cognitive systems. Let us try to decode the science behind Emotion Recognition Algorithms, and build one for ourselves.
What exactly is a cognitive emotion detection algorithm trying to accomplish? The idea is to replicate the human thought process based on training data (in the form of images and videos of humans) and try to segment the emotions present in this data. To perform our analysis in this chapter we will be concentrating on pre-recorded images and videos that showcase an emotion, but the same can also be implemented on a live stream of the video feed for real-time analytics.
Visual Understanding of the World
Computer Vision is a portion of Artificial Intelligence that deals with visual data. With the advent use of machine learning and deep learning models, computer systems today can work with digital images and videos to understand and emotionally identify the characteristics of the video’s contents.
Computer Vision as a computational concept was originally seen in the 1950s where some neural networks were used to detect edges of objects which later advanced to handwritten text, speech, and languages.
Several convoluted use cases justify the use of computer vision in today’s industry. Some very basic uses are, in an examination conducted online. A web camera can read the expressions of the user to interpret their state of mind. This is also useful in testing emotional strength for…
