Abstract
A real-time face tracking and recognition system is constructed based on Seetaface, and it is proposed to use Gamma correction to reduce the impact of illumination changes on the detection and recognition results. First, the system has face detection function, then by using OpenCV to get the image in front of the camera, the system completes the function of real-time face tracking, users can also upload local images to make face comparison. If a stranger’s face is detected, the system can collect information and train it. The system achieves multiple face tracking as well as recognition. Through the analysis and evaluation on public datasets. The improved face tracking and recognition system has a satisfactory accuracy and performance.
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