Target tracking algorithm based on scale adaptive correlation filtering and feature point matching

Abstract

The present invention belongs to the visual tracking field, and provides a target tracking algorithm based on the scale adaptive correlation filtering and feature point matching which solves a long-time target tracking problem. The target tracking algorithm comprises establishing a scale adaptive correlation filtering tracking module CFF to process each frame of image; establishing a tracking module MTF based on the feature pint matching and an optical flow; and establishing a cooperative processing determination module of the CFF and the MTF. According to the present invention, a tracking problem is decomposed into the CFF and the MTF which can assist mutually, whether the algorithm is updated is decided by determining the shielded degree of a target or determining whether the target has disappeared in the view field, thereby preventing a model from being polluted by the background information to generate a drift phenomenon. When appearing in the view field again, the target can be detected again, and the corresponding modules are updated to track continuously and stably for a long time. Moreover, the processing speed of the target tracking algorithm satisfies the real-time processing requirement completely, and the target tracking algorithm has a very good effect aiming at an actual complicated scene.

Description

technical field [0001] The invention belongs to the field of visual tracking, relates to a target tracking algorithm based on scale adaptive correlation filtering and feature point matching, and solves the problem of long-term target tracking. Background technique [0002] In recent years, with the continuous development of target tracking algorithms, most tracking algorithms can well solve the slight occlusion problem of a single target in a simple environment. However, more robust long-term, real-time tracking algorithms are still needed in more complex situations such as severe occlusion or objects leaving the field of view. [0003] Existing tracking algorithms based on correlation filtering have been able to achieve very high processing speed to meet the real-time processing requirements of target tracking, but for the occlusion problem, it is still unable to avoid target model pollution and cannot adapt to target size changes. In addition, how to select representative...

AI Technical Summary

Problems solved by technology

[0003] The existing tracking algorithm based on correlation filtering has been able to obtain a very high processing speed to ensure the real-time processing requirements of target tracking, but it still cannot prevent the target model from being polluted and cannot adapt to the size change of the target for the occlusion problem.

In addition, in the tracking algorithm based on feature point matching, how to select representative feature points to represent the target will directly affect the tracking effect, and the tracking algorithm based on feature point matching is difficult to achieve real-time processing speed, and can not remove the free objects well. point

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