Some Cases of Object Tracking Parametrs Optimization in Video Stream

Object tracking in video stream can be used in many ways such as face recognition in photos, creating deepfake videos, augmented reality. A significant part of the object tracking algorithms implemented work less accurately and more slowly than they could. The main reason for this problem lies in the insufficiently careful selection of tracker parameters. This article discusses methods for solving this problem based on the analysis of tracking algorithms both using ground truth and not. The article describes methods for evaluating various parameters of tracking algorithms, and deduces patterns that occur during the operation of tracking algorithms. As a result of the study, the performance and "efficiency" of various tracking algorithms depend on their parameters, and optimal sets of parameters were selected for working on different types of data under different performance conditions.