A Customer Service Quality Control Platform Based on User Behavior Tracking

This paper designs and implements a customer service quality control platform based on human behavior tracking, which uses surveillance video to control customer service quality. The platform includes functions such as monitoring source management, video file management, human behavior recognition, and intelligent analysis. The article first introduces the implementation of the platform's hierarchical architecture and functional modules and then uses DeepSort multi-target tracking and 3D convolution to realize multi-person behavior recognition and the quality is analyzed according to the behavior. The final results are fed back to the customer service quality control personnel to achieve intelligent service quality control.