基于WebSocket的动态人脸识别系统构建

Construction of Dynamic Face Recognition System Based on WebSocket

传统人脸识别系统的客户端与服务端交互基本上采用HTTP轮询或者定时任务触发方式,该方式不能满足动态人脸识别的实时性需求。为进一步提高识别精度和时效性,采用MTCNN多任务学习算法,构建了基于WebSocket的动态人脸识别系统。测试表明:该系统提高了人像识别率,支持浏览器与Web服务器的双向通信,能将识别出的人像信息及预警结果经服务端主动推送至客户端实时显示和告警,有效降低数据传输量,提高数据传输的稳定性和及时性。

The interaction between the client and the server of the traditional face recognition system basically adopts HTTP polling or timed task triggering,which can not meet the real-time requirements of dynamic face recognition.In order to further improve the recognition accuracy and timeliness,the dynamic face recognition system based on WebSocket is constructed by using MTCNN multi-task learning algorithm.The test shows that the system improves the portrait recognition rate,supports the two-way communication between the browser and the web server,and can actively push the identified portrait information and early warning results to the client through the server for real-time display and alarm,effectively reduce the amount of data transmission,and improve the stability and timeliness of data transmission.