The high design cost and huge computing resource demand of intelligent devices have become the main obstacles to the implementation and application of deep learning algorithm in portable and low-power devices. In order to solve these problems, in this paper, based on the raspberry PI platform and with the help of Intel video processing unit(VPU) low-power acceleration module, a real-time face detection system based on CNN model with residual feature extraction module was designed and implemented. The experimental results show that compared with using central processing unit(CPU) of raspberry PI alone, the proposed method achieved 18.62 times and 17.46 times acceleration respectively in the experiments of face detection and face alignment detection in video stream. It realized the fast, real-time and online face detection and face alignment extraction in portable devices. Meanwhile, it also provided a feasible scheme for the operation of deep learning algorithm in portable and low power devices.