An Improved Moving Target Tracking Method Suitable for Edge Computing Framework

Abstract:

With the rapid development of 5G communications technology, IoT and big data technology, traditional cloud computing models have become increasingly unable to keep up with the growth rate of data, as a new computing model, edge computing has demonstrated a strong ability to handle big data and high-speed computing. This paper propose an edge computing framework suitable for video image processing, and two improvements to the traditional moving target tracking algorithm: (1) Raspberry Pi is used as the video front-end processor, which has the characteristics of small size, low cost, and strong computing power; (2） a step-by-step image sampling method with a smaller step size as a sliding window is used to improve the original compression tracking algorithm, thereby reducing the amount of calculation. The results of computer simulation experiments show that the algorithm improves the operation speed without affecting the tracking accuracy.