Video target tracking method combining particle filtering and metric learning

Abstract

A video target tracking method combining particle filtering and metric learning belongs to the target tracking field, and comprises the following steps: offline training a convolutional neural networkcapable of effectively obtaining high-level abstract features of a target; then, learning a weighted distance metric matrix based on a kernel regression metric learning method to minimize a kernel regression prediction error, and solving an obtained optimization problem by utilizing a gradient descent method so as to obtain a distance metric matrix representing an optimal candidate target; calculating a reconstruction error based on the obtained optimal candidate target prediction value so as to construct a target observation model; finally, introducing an updating strategy combining short-time stable updating and long-term stable updating, achieving effective target tracking based on a particle filter tracking framework. The method has high target tracking precision and good robustness.

Description

technical field [0001] The invention belongs to the field of target tracking, and in particular relates to a target tracking method combined with particle filtering and metric learning. Background technique [0002] As a research hotspot in the field of computer vision, visual tracking is interested in continuous perception based on visible light and infrared media. It is one of the research hotspots in the field of computer vision and has wide applications in video surveillance, automatic driving, and human-computer interaction. In recent years, many efficient and robust visual tracking algorithms have been proposed one after another, greatly promoting the practical process of target visual tracking. However, due to the complexity of the actual scene, there are a large number of interference and uncertain factors such as illumination changes, size changes, and target occlusions in the tracking process, resulting in a significant decline in tracking performance. Therefore, ...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem that the target tracking performance is significantly reduced due to factors such as illumination changes, target deformation, and partial occlusion in complex environments, the present invention proposes a video target tracking method that combines particle filtering and metric learning, including the following steps:

Images