Facial Expression Recognition

Facial Expression Recognition (FER) has become an emerging area of interest due to advancements in the fields of Computer Vision and Artificial Intelligence.

This technology not only helps machines to recognize the human face, but also can recognize a person’s expressions – for example, to determine if someone is happy and relaxed or angry and upset. Facial expressions can be difficult to recognize because these expressions vary from face to face.

The human brain – which has the ability to recognize facial expressions – is considered the most advanced computer, and therefore efforts have been made to artificially replicate brain function. Now that many artificially-intelligent models have been developed, researchers are taking a new interest in facial expression recognition capabilities.

Many of the models that have been developed are able to accurately extract the features of the human face, but there are still areas where these models provide inaccurate readings. The challenge in developing FER models, is that there are so many differences in every face, that a generic model is hard to implement. However, with new approaches, we have been able to improve these models by reducing the complexity of the image and providing only meaningful information to the system.