A Target Tracking Algorithm Based on Correlation Filter and Least Squares Estimation

Abstract

Target tracking plays a very important role in the civil field and has always been a hot topic for scholars. But there are also problems such as the difficulty of tracking goals. The core part of the algorithm framework proposed in this paper includes target recognition and target tracking models. The target apparent model is solved by using the correlation filter-based tracking algorithm, and the reliability of the block itself is calculated by using each block response graph, and calculate the relationship between multiple blocks in the same frame, and define the contribution of each block to the overall tracking result. In order to solve the problem of difficult target tracking, the core part of the algorithm framework proposed in this paper includes target recognition and target tracking model. In this paper, a tracking algorithm based on correlation filtering is used to solve the apparent model of the target, and the reliability of each block is calculated by the response graph of each block. The experimental results show that the parallel algorithm framework designed in this paper can not only achieve stable and accurate tracking under the interference of masking, deformation and scale change, but also quotes the idea of least squares method. The models and characteristics of the previous least squares method are analyzed and summarized. The target initial value least squares estimation method is improved.