A real-time facial expression recognition based on OpenCV and Dlib model is proposed in this paper, which
avoids low recognition rate and complex extraction process in traditional methods and complex model and poor real-time
in deep learning-based methods. First, OpenCV is used to capture and pre-process images in real time. Then the Dlib
model is applied to calibrate the facial key points in the acquired face image. Finally, fifive indexes proposed in the paper,
i.e., eyebrow tilt degree, eyes open degree, upper lip to nasal tip height ratio, mouth width ratio and mouth height ratio are
combined to recognize expression. Besides, a system interface with simplifified operation is built to enhance the
practicability of the proposed method. Experiments show that the accuracy of the proposed method is above 96%, which
verififies its effffectiveness.
2023, Vol. 1 
