Multi-feature united sparse represented target tracking method

A joint sparse and target tracking technology, applied in the field of target tracking of multi-feature joint sparse representation, can solve problems such as high environmental requirements, tracking failure, and narrow adaptation range.

Inactive Publication Date: 2013-09-11
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

This method preprocesses the sample pixels before sparse coding, which improves the accuracy of target tracking to a certain extent. However, because only the gray value of the pixel is used, when the illumination changes are greatly affected or the target is seriously occluded, It will inevitably lead to the failure of tracking, high requirements on the environment, and narrow scope of adaptation

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  • Multi-feature united sparse represented target tracking method
  • Multi-feature united sparse represented target tracking method
  • Multi-feature united sparse represented target tracking method

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Embodiment 1

[0078] The multi-feature joint sparseness in step 7 in the first embodiment is based on the sparse representation of the original feature vector. However, in many vision problems, feature descriptions (vectors) are often encoded in the form of kernel matrices. In order to combine multiple kernel features, we extend the original feature space to RKHS to revisit the sparse representation problem.

[0079] The kernel function technique consists in: for each feature k, use a non-linear function φ k Map the dictionary template and candidate samples from the original feature space to another high-dimensional RKHS, in this high-dimensional space, for some given kernel function g k , with φ k (x i ) T φ k (x j ) = g k (x i ,x j ). In the new space, we rewrite the formula (1) in Step 7 of Embodiment 1 as:

[0080] min W 1 2 Σ k = 1 ...

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Abstract

The invention provides a multi-feature united sparse represented target tracking method. The multi-feature united sparse represented target tracking method comprises building a primary dictionary; performing partitioning process on target modules; extracting candidate particles; extracting target characteristics; confirming the number of image characteristics and the number of block categories; performing nucleating process on the characteristics; performing block sparse representation on candidate samples in the dictionary; performing nucleus expansion; solving sparse problems; performing residual calculation on blocks; building likelihood functions; and updating template bases. The multi-feature united sparse represented target tracking method is analysis and improvement of utilized target characteristics and the traditional sparse coefficient solving method through a sparse encoding tracking device. According to the multi-feature united sparse represented target tracking method, stability of target tracking is maintained and accuracy of the target tracking device is improved under complex conditions that the illumination influence is large and the target is seriously shielded, and the accuracy of the algorithm and stability of the tracking are improved.

Description

technical field [0001] The invention belongs to the technical field of computer image processing, and relates to a target tracking method, more specifically, relates to a target tracking method of multi-feature joint sparse representation. Background technique [0002] Visual target tracking refers to the technology of continuously inferring the trajectory of a specific target's motion state from the video sequence recorded by the camera. It is a very important research topic in computer vision research and can be used in many application fields such as automatic monitoring, robot navigation, and human-machine interface. . Object tracking not only promotes theoretical research in the fields of image processing, pattern recognition, machine learning and artificial intelligence, but also becomes an indispensable part of many practical computer vision systems. Although object tracking is a very simple task for the human visual system, the performance of existing tracking algor...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20H04N5/14
Inventor 胡昭华吴佑林徐玉伟赵孝磊
Owner NANJING UNIV OF INFORMATION SCI & TECH
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