K sparseness based rapid robust target tracking method

A target tracking and robust technology, which is applied in the field of fast and robust target tracking based on K sparse, can solve the problems of not meeting the real-time requirements of target tracking and the large amount of calculation, and achieves improved accuracy, improved real-time performance, and accurate tracking. the effect of the result

Active Publication Date: 2018-03-09
SHAOGUAN COLLEGE
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  • Application Information

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Problems solved by technology

However, since the sparse cooperative robust target tracking method uses LASSO to solve l 1 Optimization problem, and the LASSO solution process has a large amount of calculation, which cannot meet the real-time requirements of target tracking

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Embodiment 1

[0072] see figure 1, the present invention provides a fast and robust target tracking method based on K-sparse, comprising the following steps:

[0073] S1: Obtain the first frame image and the current frame image, and obtain the first frame target area of ​​the first frame image.

[0074] In the step S1, the first frame image and the current frame image are input into the relevant processing device through an external camera device or storage device, so that the processing device can acquire the continuous first frame image and the current frame image; and, the acquired The target area of ​​the first frame essentially obtains the position parameter of the area occupied by the target to be tracked in the first frame image, and the position parameter is obtained by inputting to the processor.

[0075] S2: Establish a positive and negative template dictionary A according to the first frame image and the first frame target area, and generate a redundant dictionary D according to...

Embodiment 2

[0131] The fast robust target tracking method based on K-sparse in this embodiment is basically the same as the fast robust target tracking method based on K-sparse in Embodiment 1, the only difference is that this embodiment adds Steps S10 and S12, in order to update the positive and negative template dictionary and redundant dictionary as the basis of discrimination according to certain rules in the process of realizing the target tracking, so as to ensure the applicability and accuracy of the basis of discrimination, which is more conducive to the target in subsequent images Tracking is analyzed and processed, and more accurate tracking results can be obtained. see figure 2 Compared with the target tracking method in embodiment 1, the K-sparse fast and robust target tracking method in this embodiment 2 further includes the following steps:

[0132] S10: Determine whether the frame number of the current frame image is an integer multiple of N, if yes, execute step S11, oth...

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Abstract

The invention relates to a K sparseness based rapid robust target tracking method. The K sparseness based rapid robust target tracking method comprises the following steps: solving a sparse matrix byutilizing a positive and negative template dictionary; solving an optimization problem of the positive and negative template dictionary l1 by utilizing the sparse matrix, namely K sparseness, whereinunder the condition that the sparseness is relatively small and the signal-to-noise ratio is the same, the speed of solving a sparse coefficient is 10 times or more than 10 times of an LASSO (Least Absolute Shrinkage and Selection Operator) algorithm; dividing a current-frame image into a plurality of image samples and calculating a reconstruction error by utilizing a normalized positive templatematrix and a normalized negative template matrix; judging error parameters through reconstruction and comparing samples obtained by histograms, so as to realize target tracking in the current-frame image. Therefore, the target tracking accuracy is also improved, a more accurate tracking result can be obtained and the instantaneity of tracking is improved.

Description

technical field [0001] The invention belongs to the technical field of video image processing, in particular to a fast and robust target tracking method based on K-sparse. Background technique [0002] Target tracking is a method of estimating the target state in a video or image sequence, which plays a very important role in many machine vision applications, such as motion analysis, behavior detection, video surveillance, traffic monitoring, medical image processing, etc. effect. Although the target tracking technology has made great progress in recent decades, how to provide a robust and fast target for some complex dynamic scenes due to brightness changes, camera shake, target occlusion, and target shape position changes? Tracking methods remain a huge challenge in the field of computer vision. [0003] Currently, for target visual tracking, there are mainly two tracking models—morphological model and motion model. Among them, the morphological model is used to represe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/246G06K9/46
CPCG06T7/246G06V10/40G06V10/513
Inventor 杨森泉周永明陈景华陈锦儒文昊翔罗欢
Owner SHAOGUAN COLLEGE
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