Computer Vision-Based Analysis of Teacher–Student Interaction Behaviors in Dynamic English Classroom Environments

Under the framework of educational informatization, dynamic classroom environmentscharacterized by flexible spatial layouts and integrated multimedia interaction technologies-have emerged as pivotal settings for English language instruction.Teacherstudent interaction, as a core component of the instructional process, encompasses diverse verbal and non-verbal communication patterns that significantly influence both pedagogical effectiveness and student learning experiences.The advancement of computer vision enables more precise analysis of such interactive behaviors; however, current approaches remain limited.Methods relying on single-view visual data often fail to comprehensively capture the complexity of classroom interactions, resulting in incomplete behavioral recognition.Furthermore, traditional handcrafted feature extraction techniques have shown limited capacity in capturing dynamic motion cues, thereby reducing recognition accuracy in diverse classroom postures and gestures.To address these limitations, a multiview fusionbased method for recognizing teacher-student interaction behaviors in English classrooms was proposed.The model comprises a multiview fusion module and a motion feature extraction module.The former integrates visual information from multiple camera angles to mitigate single-view occlusion and information loss, while the latter leverages deep learning to effectively model dynamic bodily expressions and postural transitions.Experimental results demonstrate that the proposed method significantly enhances recognition accuracy of interactive behaviors in dynamic classroom environments.This approach provides a robust data-driven foundation for optimizing instructional strategies, supporting personalized learning, and informing intelligent classroom design.The findings contribute both theoretical insights and practical value to the integration of computer vision technologies in English language education.