Emotion Recognition Based on Facial Landmarks
By: Raub Camaioni, Harnaik Dhami, Philip Guzik, Kevin Yu
Summary
In the world of machine learning there are many complex issues that come along with emotional recognition. Many issues such as what facial features you should try to extract, different facial forms and what type of emotions can be differentiated. There have been many advances in computer vision as well as machine learning algorithms, but our group aims to analyze multiple methods of emotion detection that can optimize the detection of emotional state based off of facial features. We will look at the different methods in which to extract facial features and compare prediction accuracy between machine learning algorithms.
Motivation
Recognizing emotion has many potential impacts. For example, emotion can be used by advertisement companies to see whether the target user enjoys a particular ad. There are many other use cases similar to this. Recognizing emotion shown by patients in a hospital can help notify the nursing staff if the patient is showing pain. The benefits of detecting the emotion of a person is countless in our society.
Acknowledgement
We would like to give a big thanks to our professor Bert Huang for teaching us many different machine learning methods and the many pro's and con's that come with machine learning.