Embedded Face Recognition System Based on Multi-task Convolutional Neural Network and LBP Features

Based on neural network and local binary pattern algorithm, this paper builds a lightweight artificial face recognition system on chip Firefly-RK3399, with high speed, strong robustness and high recognition accuracy. Our embedded artificial intelligent face recognition system mainly consists of face detection, feature extraction and recognition. Multi-task convolutional neural network (MTCNN) under the CaffeOnACL framework is utilized for face detection, and the local binary pattern (LBP) is applied as face recognition algorithm. Experiments illustrate that our artificial intelligent embedded face recognition system has high speed and accuracy, which is easy-carrying and of high commercial value as well.