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Density adaptive clustering method orienting behavior identification

A clustering method and adaptive technology, applied in the field of data identification, can solve problems such as limiting the scope of application

Inactive Publication Date: 2016-06-08
NORTHWESTERN POLYTECHNICAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Its above-mentioned deficiencies limit its scope of application

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  • Density adaptive clustering method orienting behavior identification
  • Density adaptive clustering method orienting behavior identification
  • Density adaptive clustering method orienting behavior identification

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Embodiment Construction

[0027] The present invention will be described in detail below in conjunction with the drawings.

[0028] Such as figure 1 As shown, the present invention provides a density adaptive clustering method for behavior recognition, including the following steps:

[0029] 1) Set density levels and the highest and lowest density thresholds, and calculate the density thresholds at each level according to the set density levels and the highest and lowest density thresholds;

[0030] The step 1) is specifically:

[0031] Set the density level DensityLevel, the lowest density threshold (ε l , MinPts l ), the highest density threshold (ε h , MinPts h ), according to the set density level DensityLevel, set multiple density thresholds (ε i , MinPts i ), i=1, 2, ..., where:

[0032] Eps i = Eps h - ( i - 1 ) * Eps h - Eps l D e n s i t y L e v e l MinPts i = MinPts h - ( i - 1 ) * M...

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Abstract

The invention discloses a density adaptive clustering method orienting behavior identification, and relates to the technical field of clustering analysis. The density adaptive clustering method comprises the steps that clustering analysis is performed on a given data set from the highest density threshold to the lowest density threshold according to the decreasing order. The result generated in the previous clustering process can directly act as the input of the next clustering process, and necessary correction is performed on the previous clustering result under the current density threshold so that clustering of different density data clusters can be realized. Basic clustering operators adopt the clustering method based on density, and the clustering process is the typical iterative extension process so that the disadvantages that a distance-based algorithm only can discover quasi-circular clusters can be overcome. Therefore, the method is not sensitive to noise data and can automatically eliminate influence of the noise data on the clustering process and can discover the clusters of any shapes.

Description

Technical field [0001] The invention relates to the technical field of data recognition, in particular to a density adaptive clustering method for behavior recognition. Background technique [0002] The density-based clustering method is an important branch based on the clustering method, which mainly performs clustering by measuring the number of points contained in a region. The classic density-based clustering methods mainly include DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and OPSTICS (Ordering Points to Identify the Clustering Structure). The main advantages of traditional density-based algorithms are as follows. 1. It is not sensitive to noise data and can automatically eliminate the influence of noise data on the clustering process. 2. Can find clusters of any shape. Because the clustering process is a typical iterative expansion process, it can overcome the shortcomings that the distance-based algorithm can only find clusters like circular cl...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/232
Inventor 倪红波王天本周兴社张大庆王柱贾江波
Owner NORTHWESTERN POLYTECHNICAL UNIV