Facial Expression Recognition using Deep Learning
This work addresses the problem of robust facial expression recognition for applications in non-verbal communication, but it appears incremental as it applies existing deep learning methods to a known dataset.
The paper tackles facial expression recognition on challenging datasets with partial faces, specifically using the FER-2013 dataset, and reports that deep learning models achieve significant improvement over traditional approaches and some existing deep learning models.
Throughout the various ages, facial expressions have become one of the universal ways of non-verbal communication. The ability to recognize facial expressions would pave the path for many novel applications. Despite the success of traditional approaches in a controlled environment, these approaches fail on challenging datasets consisting of partial faces. In this paper, I take one such dataset FER-2013 and will implement deep learning models that are able to achieve significant improvement over the previously used traditional approaches and even some of the deep learning models.