Real-time tracking method of multi-channel kernelized correlation filter

Abstract

The invention discloses a real-time tracking method of a multi-channel kernelized correlation filter. The method includes the following steps: a training step of conducting ridge regression on a previous frame of object information to acquire a filtering template; a detection step of detecting the current frame of image with the acquired filtering template and outputting a filtering response; an updating step of real-time updating the filtering template and the appearance of an object. According to the invention, the method uses kernel function to fuse multi-channel characteristics, overcomes the selection limit of the multi-channel characteristics, and transforms the problem of linear optimization of ridge regression to the problem of non-linear optimization of a higher space through the kernel function, such that the filtering template with excellent robustness is constructed, the speed of a tracking machine is greatly increased, and tracking requirements of real world can be met.

Description

technical field [0001] The invention belongs to the field of image processing and computer vision, and in particular relates to a real-time tracking method of multi-channel kernel correlation filtering. Background technique [0002] In computer vision, object tracking is a fairly extensive research field, and it has a very wide range of applications in the fields of automatic monitoring, video indexing, traffic monitoring, and human-computer interaction. Although researchers have proposed many algorithms in the past decade, how to build a stable and efficient tracking system to deal with the appearance changes, fast motion, scale changes and occlusions of objects is still a challenging task. [0003] Most of the existing high-precision trackers build complex appearance models and extract a large number of candidate particles, and calculate the similarity or confidence value between each candidate particle and the tracking result of the previous frame through traversal. Ther...

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Problems solved by technology

[0005] The technical problem to be solved in the present invention is to fuse multi-channel features through kernel functions, extend linear correlation filtering to nonlinear correlation filtering, and propose a real-time tracking method for multi-channel kernel correlation filtering to ensure that the tracker can track in complex real-world scenarios. , such as occlusion, illumination changes, appearance changes, etc., it can still track the target accurately and quickly

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