Abstract: We present the design of face identification system that can run in real time environment. We use multiple contexts to optimize the face recognition performance in real time. Initially different illumination environments are modeled as context using unsupervised learning and accumulated as context knowledge. Optimization parameters for each context are learned using Genetic Algorithm (GA).GA search the optimization parameter so as to minimize the effect of illumination variation. These weight parameters are used during similarity match of face images in real time recognition. Gabor wavelet is used for facial feature representation. Experiment is done using real time face database containing images taken under various illumination conditions. The proposed context aware method has been shown to provide superior performance than the method without using context awareness.