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Online Classification Method of Target Behavior Patterns Based on Inductive Consistency Multiclass Classification

A classification method and consistent technology, applied in character and pattern recognition, instruments, calculations, etc., can solve the problem of not fully utilizing the position, speed and heading characteristics of the target, and the large amount of calculation, achieving high accuracy and reducing calculation. Simple effect of quantity and parameter setting

Active Publication Date: 2020-03-17
NAVAL AVIATION UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

Many scholars at home and abroad have studied the problem of trajectory classification, but these methods mainly consider the position and shape characteristics of the target, and do not make full use of the position, speed and heading characteristics of the target, and the existing methods are mainly used for offline classification. It is not applicable to the field of early warning and monitoring with high real-time requirements
The online classification method of target behavior patterns based on multi-dimensional features can make full use of the target's position, speed and heading characteristics, and realize the online classification and discrimination of target behavior patterns through online learning and sequential classification of multi-dimensional track data. All historical track data need to be recalculated during classification and discrimination, and there is a problem of large amount of calculation

Method used

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  • Online Classification Method of Target Behavior Patterns Based on Inductive Consistency Multiclass Classification
  • Online Classification Method of Target Behavior Patterns Based on Inductive Consistency Multiclass Classification
  • Online Classification Method of Target Behavior Patterns Based on Inductive Consistency Multiclass Classification

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Embodiment Construction

[0025] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0026] Step 1, define related variables:

[0027] 1) The number k of neighbors to be considered;

[0028] 2) Training track data set where l 1 +…+l t +…+l s = l, 1, 2,..., s is the category label, l is the total number of training tracks, compressed track data set r 1 ,...r t ,...,r s To compress the number of tracks, check the track dataset

[0029] 3) Multi-factor oriented Hausdorff distance matrix M1,...,Mt,...,Ms, where each element M1 of matrix M1 i,j :i=1,...,l 1 -r 1 ,j=1,...,k represents the test track data set Track TR in 1i :i=r 1 +1,...,l 1 to the compressed track data set The multi-factor directional Hausdorff distance between the jth closest track, each element in M2,...,Ms is the same;

[0030] 4) Empty priority sequence Q1,...,Qt,...,Qs;

[0031] 5) Test track TR l+1The constantly updated track point x in 1 ,......

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Abstract

The invention discloses an online classification method for target behavior patterns based on inductive consistency multi-category classification. The method includes: step 1, defining relevant variables; step 2, initialization; step 3, using one of the categories of training track data sets and compressed track data sets, to calculate the current track point in the test track p value; step 4, repeat step 3, calculate the current track point corresponding to other categories p value; step 5, compare all categories corresponding to p The size of the value determines the target behavior pattern category corresponding to the current track point; step 6, after the target behavior pattern corresponding to each track point of the current test track is classified, update the training track data set; step 7, update Multi-factor directional Hausdorff distance matrix; step 8, classify the target behavior pattern corresponding to the next test track. This method can realize the online classification and discrimination of the target behavior pattern while reducing the amount of calculation, and has broad application prospects.

Description

technical field [0001] The invention relates to an online classification technology in data mining and a high-level fusion technology in information fusion, and belongs to the field of pattern recognition and intelligent information processing. Background technique [0002] In the field of early warning and surveillance, with the continuous improvement of target detection technology and information fusion technology, various targets are detected, tracked and identified, forming a constantly updated target track. A large amount of historical track data is stored and accumulated in various target intelligence processing systems in the field of early warning and surveillance. Using data mining and cluster analysis technology in trajectory data mining, the target track can be divided into different categories, so as to dig out the behavior rules of the target. The behavior pattern of the target refers to the category of the target behavior law that the current observation targe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/2431G06F18/214
Inventor 潘新龙王海鹏何友
Owner NAVAL AVIATION UNIV
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