We present a fully automatic real time system for face detection and basic facial expression recognition from video and images. The system automatically detects frontal faces in the video stream or images and classifies each of them into 7 expressions. Each video frame is first scanned in real time to detect upright-frontal faces. The faces found are scaled into image patches of equal size and sent downstream for further processing. Gabor energy filters are applied at the scaled image patches followed by a recognition engine. Best results are obtained by selecting a subset of Gabor features using AdaBoost and then training Support Vector Machines on the outputs of the features selected by AdaBoost.