We present a real-time face recognition system that we implemented on a cell-phone using computationally efficient Minimum Average Correlation Energy Filters. We examine the challenges faced in realizing such a practical system that can perform both enrollment and verification in real-time on the cell-phone using its limited memory and computational resources. Due to the speed and memory constraints of the cell-phone, we optimize the Correlation Filters using a fast fixed-point implementation of 2D Fourier Transform optimal for the cell-phone platform. We also detail an efficient algorithm for synthesizing these filters efficiently in order to minimize computation load and making the system practical with real-time enrollment of users.