Research on Classroom Teaching Quality Evaluation Method Based on Machine Vision Analysis

Concentration is one of the key factors human intelligent behaviour. Especially in recent years, our attention to learners has received extensive attention. Many evaluation methods are put forward for concentration, including questionnaire, physiological observation and computer vision. In classroom primary secondary schools, students' concentration class an important factor that affects achievement teaching effect, so it a major concern many parents. Firstly, analytic hierarchy process used construct index system, then multi-population genetic algorithm optimize design BP neural network, finally network evaluate quality. traditional environment, participation research mostly obtained through questionnaires designed after class. The lack real-time learning monitoring analysis far from meeting needs modern education development. Therefore, there urgent need Research on automatic state method uses artificial intelligence technology full whole process, assist teachers understand master state, adopt targeted methods, improve personalized training level.