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A target tracking method based on multi-task joint sparse representation

A joint sparse and target tracking technology, which is applied in the field of target tracking based on multi-task joint sparse representation, can solve problems such as inability to merge together, and achieve the effect of robust tracking results

Active Publication Date: 2015-09-30
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
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Problems solved by technology

However, under the traditional sparse representation framework, these features cannot be effectively fused together.

Method used

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  • A target tracking method based on multi-task joint sparse representation
  • A target tracking method based on multi-task joint sparse representation
  • A target tracking method based on multi-task joint sparse representation

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Embodiment Construction

[0016] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0017] The specific operating hardware and programming language of the method of the present invention are not limited, and can be completed in any language.

[0018] figure 1 It is a flowchart of the method provided by the present invention.

[0019] Step 1: At the beginning of tracking, construct different template sets for different features of the target to be tracked;

[0020] Step 2: The template set of each feature is modeled with a sparse representation task, and a multi-task joint sparse representation model based on a local sparse graph is constructed;

[0021] Step 3: Iteratively solve the multi-task model by using the approximate accelerated nearest neighbor gradient algorithm;

[0022] Step 4: Use the vari...

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Abstract

The invention discloses a tracking method on the basis of multitask combined sparse representation, which comprises the following steps of: when starting to track, respectively constructing different template sets for different characteristics of a target which needs to be tracked; modeling for the template set of each characteristic by one sparse represented task to construct a multitask combined sparse representation model on the basis of a local sparse graph; carrying out iteration solution on the multitask model by adopting an approximate accelerated neighbor gradient algorithm; selecting weights of different tasks by using a variance ratio; and constructing an appearance model on the basis of multitask combined sparse representation and estimating an optimal state of the target, which is used as a tracking result, by adopting a particle filter algorithm.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to an object tracking method based on multi-task joint sparse representation. Background technique [0002] The motion tracking of targets in complex scenes is one of the cutting-edge research directions in the field of computer vision in recent years, and it is also one of the difficulties in this field. Especially the target motion analysis in dynamic scenes has been highly valued by many important research institutions in the world. The tracking problem is equivalent to the problem of creating correspondence matching between consecutive image frames based on relevant features such as position, velocity, shape, texture, color, etc. As we all know, the core of region tracking is how to effectively express the target, and most of the target expression is achieved through target appearance modeling. Therefore, how to construct a good appearance model plays a crucial role in the regio...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/20
Inventor 胡卫明李威
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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