Data Room Management System Based on Target Detection Algorithm

Abstract

In recent years, streaming media services have been widely used in data room management systems. In order to record the user operations, host machine alarms and reminder in real time, target detection algorithms for streaming media have played an important role. Conventional target detection methods, limited by detection speed, are not suitable for such real-time application. So, in this paper, we applies SSD (Single Shot MultiBox Detector) algorithm to data room management system. Firstly, we constructs a host operating image data set, and then perform data amplification by adding noise and rotation. Secondly, the SSD model is used to train a model. Finally, after obtaining the target detection results, the NMS (Non-Maximum Suppression) algorithm is used to avoid the redundant detection frame. At the same time, some improvement measures are put forward to solve the problem of small target, leading to the difficulty of feature extraction and low detection accuracy. The experimental results demonstrate that the model can detect and track the target better in the video and meet the requirements of the real-time performance and accuracy of the system.