Tracking missing objects in a video using yolo3 in cloudlet network.
Published in Smart Technologies in Data Science and Communication , 2021
In real time, people are using CCTV for monitoring activities continuously but sometimes theft is taking place. In this scenario, people need to roll back the video and need to identify when it happened. But in practice, it is a difficult and time-consuming process to identify a missing object in the video within the local machine because of the lack of computing resources. To solve this problem, we are presenting an algorithm in this paper to notify missing objects in a video offloaded from a mobile or CCTV using YOLO3 object detection in a cloudlet network. In the area of cloud computing, a cloudlet is a data center in the local network with a rich set of computing resources available for mobile users.
Recommended citation: K. Boddu, S. M, and S. N. “Tracking missing objects in a video using yolo3 in cloudlet network.
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