Introduction
Recently, face recognition (FR) is widely adopted to mobile devices as a measure for user identification, enabling user-spe-cific services. The convolutional neural network (CNN) shows high accuracy in FR, so that a dedicated CNN FR processor was developed to reduce power consumption in battery-limited environment [1]. However, variance in head pose causes accuracy degradation for stand-alone CNN up to 10% [2], as shown in Fig. 1. Face alignment which converts the input face into its frontal face can enhance the recognition accuracy, but its software realization on mobile application processors consume >1W power, greatly diminishing battery run-time. The necessity of the face alignment hardware was first raised in [3], but only simulated results were given. Therefore, a low-power FR processor with face aligning capability is necessary for high accuracy mobile FR system.