Application of entertainment e-learning mode based on genetic algorithm and facial emotion recognition in environmental art and design courses

Abstract

This article is based on facial recognition and further designs an entertainment electronic learning mode. Facial emotion recognition may be affected by light, angle, and expression. In order to improve recognition accuracy and stability, distortion adjustment techniques were used to process facial images, ensuring that the model can accurately capture and recognize the features of facial expressions. The study applies online facial emotion recognition to entertainment electronic learning modes, where learners interact with the system. The system can detect and recognize learners’ facial expressions in real-time, and provide corresponding feedback and learning resources based on different expressions. By collecting and analyzing experimental data, evaluate the practicality of the model and the level of acceptance and satisfaction of learners towards the model. The entertainment electronic learning mode based on facial recognition provides an innovative learning approach by constructing a pattern architecture, distortion adjustment, and applying online facial emotion recognition. By optimizing the positioning and integrating the entertainment electronic learning mode with environmental art and design courses, we aim to enhance students’ learning motivation and interest. Develop optimization strategies to enhance students’ comprehensive abilities in the field of environmental art and design.