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Moving target tracking method and system

A technology for moving targets and targets, applied in the Internet field, and can solve problems such as poor performance

Inactive Publication Date: 2018-02-23
CHINA UNITED NETWORK COMM GRP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, in practical applications, it is found that the current mobile tracking methods and systems based on generative models have poor performance in a variety of complex tracking scenarios.

Method used

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  • Moving target tracking method and system

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Experimental program
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Embodiment 1

[0102] figure 1 Please refer to Figure 1 for the flow chart of the moving object tracking method provided by the embodiment of the present invention. The moving object tracking method provided by the embodiment of the present invention includes the following steps:

[0103] S1. Determine multiple target candidates (that is, target candidate regions) on the current frame.

[0104] Specifically, the tracking method proposed by the present invention is implemented based on the particle filter tracking framework, so each particle corresponds to an area on a frame image, and each area is defined by the following motion state variables:

[0105] s={x,y,σ} (Formula 1)

[0106] Where x and y represent the two-dimensional coordinates of the region on the image, and σ represents the scale parameter of the region.

[0107] The motion state variable of each target candidate region in the current frame can be inferred based on the information of the previously located target.

[0108] T...

Embodiment 2

[0241] image 3 The functional block diagram of the moving object tracking system provided by the embodiment of the present invention. see image 3 , the mobile target tracking system provided by the embodiment of the present invention, comprising:

[0242] The candidate selection module 10 is configured to determine multiple target candidates on the current frame.

[0243] The sample determination module 11 is used to determine a preset number of recently positioned targets as target samples, and obtain a series of background samples by sampling near the latest positioned target.

[0244] Learning module 12 is used for constructing subspace and training to obtain a linear classifier according to the target sample and the background sample.

[0245] The classification reliability acquisition module 13 is used to reconstruct each of the target candidates via the subspace, and use the linear classifier to obtain the classification reliability of the reconstructed target candi...

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Abstract

The invention provides a moving target tracking method and system. The method comprises the steps of determining a plurality of target candidates on a current frame; determining a preset quantity of recently located targets as target samples, and performing sampling near a newest located target to obtain a series of background samples; according to the target samples and the background samples, constructing subspaces and performing training to obtain a linear classifier; reconstructing the target candidates through the subspaces, and obtaining classification reliability of the reconstructed target candidates by using the linear classifier, wherein the classification reliability serves as a factor of judging the possibilities that the target candidates become the targets; and determining the target candidate with the maximum possibility as the target. The advantages of subspace learning and discriminative learning methods are combined, so that the performance in multiple complicated tracking scenes can be improved.

Description

technical field [0001] The invention belongs to the technical field of the Internet, and in particular relates to a method and system for tracking a moving target. Background technique [0002] Moving object tracking has become one of the core technologies in the field of intelligent technology, such as automatic video monitoring of vehicles involved in accidents in intelligent transportation, automatic tracking of moving human bodies in intelligent entertainment equipment, etc. [0003] From the perspective of model construction methods, object tracking models are divided into generative and discriminative. Among them, the generative model is to find a candidate target that best matches the target appearance model as the current target; the discriminative model is to train a binary classifier to separate the target from the background. In tracking applications, if enough target and background samples can be obtained, the discriminative model has certain advantages. However...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06T7/254
CPCG06T7/254G06V20/40G06F18/213G06F18/214
Inventor 汤雅妃王志军邓瑞李伟杰
Owner CHINA UNITED NETWORK COMM GRP CO LTD
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