This document reviews techniques for emotion recognition from facial expressions. It begins by outlining the general steps of emotion recognition systems as face detection, feature extraction, and classification. Popular techniques discussed include principal component analysis (PCA), local binary patterns (LBP), active appearance models, and Haar classifiers. PCA generally provides higher recognition rates but LBP has lower computational complexity. The document concludes PCA has the best performance among the discussed techniques. It provides a table comparing the techniques and their performance as reported in various other papers.