Robust video object tracking method

Abstract

The method discloses a robust video object tracking method, and the method comprises the steps: sampling a candidate target particle based on the particle filter importance sampling principle; filtering out divergent particles based on the cosine similarity between the candidate target particle and a former tracking result; representing the screened candidate target particle based on a template dictionary linearly; building a low-rank sparse mathematic model of a linear coefficient matrix; solving a coefficient matrix based on an incorrect lagrangian multiplier optimization algorithm; selecting an optimal candidate object according to a discrimination function to serve as a tracking result; and updating the template dictionary in an on-line manner. The robustness of the method guarantees that the method can meet various types of challenges, and achieves the accurate tracking of a target in a video. The method solves a problem of inaccurate tracking and drift of the target in the video, wherein the problem is caused by illumination variation, scale change, shading, deformation, movement fuzzy, quick movement, rotation, background clutter, low resolution and others.

Description

technical field [0001] The present invention relates to the field of computer vision, in particular to a method that can cope with various challenges such as illumination changes, scale changes, occlusion, deformation, motion blur, fast motion, rotation, background clutter, and low resolution of target objects in videos. Robust video object tracking method for continuous and accurate object tracking. Background technique [0002] Video object tracking is an important link in computer vision system, which integrates the theoretical knowledge of image processing, stochastic process, artificial intelligence and other fields. Object tracking is to use the color, texture, edge, outline and other characteristics of the specified target to detect the target, use the tracking algorithm to estimate the current state of the target's motion, and predict the state of the next moment, so as to realize the specified target. Accurate, stable, and fast tracking, obtain the motion parameter...

AI Technical Summary

Problems solved by technology

[0004] In view of the important application value of video object tracking technology, academia and companies have conducted extensive research on it, with a research and development history of more than 20 years, but there is still no good tracking algorithm model that can accurately track objects in real time. track

The main reason is that there are various challenges in tracking objects such as lighting changes, scale changes, occlusions, non-rigid object deformations, motion blur, fast motion, rotation, objects leaving the view, background clutter, low resolution, etc., which seriously affect the Tracking accuracy and design algorithm complexity

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