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A method and system for target tracking based on dynamic measurement matrix

A dynamic measurement and target tracking technology, applied in the field of computer vision, can solve problems such as feature mode solidification and tracking drift, and achieve strong adaptability and good robustness

Active Publication Date: 2017-11-07
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

However, in the CT algorithm, the measurement matrix will not change after initialization, resulting in the solidification of the characteristic mode, resulting in tracking drift in some scenarios
The invention patent with the application number CN201410660331.8 and the name "A Video Target Tracking Method Based on Compressed Sensing" uses the CT algorithm. However, this application always uses this matrix to achieve feature compression throughout the tracking process, that is to say Keeping the sparse matrix unchanged throughout the tracking process leads to the solidification of the characteristic mode, causing tracking drift in some scenarios

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  • A method and system for target tracking based on dynamic measurement matrix
  • A method and system for target tracking based on dynamic measurement matrix
  • A method and system for target tracking based on dynamic measurement matrix

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[0055] The technical solution of the present invention will be described in further detail below in conjunction with the accompanying drawings: figure 1 As shown, a target tracking method based on a dynamic measurement matrix includes the following steps:

[0056] S1: Compress the high-dimensional features of the sample into low-dimensional features, and initialize the dynamic measurement matrix;

[0057] S2: Collect multiple positive sample sets and negative sample sets around the target location, and perform classifier update learning;

[0058] S3: Determine the position of the target in the current frame;

[0059] S4: Update the dynamic measurement matrix, and return to step S2 until the tracking is completed.

[0060] Step S1 includes the following sub-steps:

[0061] S11: Put the sample High-dimensional features Compressed into low-dimensional features which is:

[0062] v=R(t)x;

[0063] In the formula, where m = (wh) 2 , N Is the dynamic measurement matrix;

[0064] S12: Initiali...

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Abstract

The invention discloses a target tracking method and system based on a dynamic measurement matrix, which includes the following steps: S1: compress the high-dimensional features of the sample into low-dimensional features, and initialize the dynamic measurement matrix; S2: collect multiple A set of positive samples and a set of negative samples are used to update the classifier; S3: determine the position of the target in the current frame; S4: update the dynamic measurement matrix, and return to step S2 until the tracking is completed. The present invention uses the dynamic measurement matrix to extract the compressed features of the target in the tracking process, that is, in the tracking process, the feature of the tracked target and the characteristics of the naive Bayesian classifier are used to update the measurement matrix, and the fixed form of the measurement matrix is ​​improved. This tracking method has strong adaptability. Experimental results prove that the tracking method has good robustness.

Description

Technical field [0001] The invention relates to the field of computer vision, in particular to a target tracking method and system based on a dynamic measurement matrix. Background technique [0002] Target tracking based on video or image sequence is one of the hot issues of computer vision, and it is very closely related to target detection. Tracking-by-detection methods also benefit from the efficiency and accuracy of detection problems. Promote. There are many difficulties to deal with the target tracking problem, such as lighting changes, target shape or posture changes, and complex scenes, which have a great impact on the tracking effect. [0003] Tracking problems can be roughly divided into two categories. One type is tracking based on generative models. This type of method learns the appearance model of the target. When searching for the target position, it looks for the area that is closest to the model or has the smallest reconstruction error; the other type is trackin...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/20
CPCG06T2207/10016
Inventor 程洪王润洲李静杨路
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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