WoT ‐based Gaussian process multi‐view learning for real‐time monitoring and identification
Aili Zhou · Internet Technology Letters · 2022
With the rapid development of imaging and communication technology, monitoring equipment is becoming more and more popular, and how to realize the real‐time monitoring and identification of key figures has become an important research direction. However, the traditional monitoring and identification systems usually upload the collected data to the server directly, and then the monitoring staff manually identifies them, or uses the artificial intelligence algorithm to identify the data stored in the past, which may lead to missed detection or false detection, and the data uploading manner will take a lot of time, so that the final identification result does not have real‐time. To solve these issues, based on the Web of Things (WoT) technology, a Gaussian process multi‐view learning system is proposed in this paper. Specifically, the Gaussian process is first used to learn multi‐view fusion features, and the identification is carried out based on these fusion features. Secondly, according to the identification results, only the monitoring data of key figures or suspected key figures are uploaded to the server and displayed at the monitoring end, so as to effectively reduce the amount of data to be transmitted. Experimental results show that the proposed Gaussian process multi‐view learning algorithm can effectively identify multi view face images.