This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. The comparative study of Facial Expression Recognition (FER) techniques namely Principal Component’s analysis (PCA) and PCA with Gabor filters (GF) is done. The objective of this research is to show that PCA with Gabor filters is superior to the first technique in terms of recognition rate. To test and evaluates their performance, experiments are performed using real database by both techniques. The universally accepted five principal emotions to be recognized are: Happy, Sad, Disgust and Angry along with Neutral. The recognition rates are obtained on all the facial expressions.