Research on Human Eye Detection Based on Actor Model

Facial recognition and eye detection applications in campus anti-bullying alarms can effectively identify students' eye movements and facial expressions. When combined with voice print recognition, they can more effectively prevent campus bullying. These devices need to quickly, accurately, and reliably detect human eyes. This paper presents an implementation method of an eye detection system based on the Actor model. By optimizing the Harr-like rectangle feature and the implementation method of the Adaboost algorithm in computers, the detection rate and reliability are improved. Introducing the Actor model allows for optimization of the system code framework using C# and.Net advantages. Experimental results demonstrate that this system exhibits high concurrency, low coupling, easy expansion, fast response time, high recognition rate, strong reliability, and lightweight characteristics which better meet application requirements in face recognition.