Target behavior mode online classification method based on multi-dimension features
A technology of multi-dimensional features and classification methods, applied in character and pattern recognition, instruments, calculations, etc., can solve the problem of not making full use of the target's position, speed, and heading features, and achieve high accuracy and simple parameter settings.
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[0028] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0029] Step 1: Define related variables:
[0030] 1) The number k of neighbors to be considered;
[0031] 2) Training track data set where l 1 +…+l t +…+l m =l, 1, 2,..., m is the behavior pattern category label of the target corresponding to the track in the training track data set, and l is the total number of training samples;
[0032] 3) Multi-factor oriented Hausdorff distance matrix M1, M2,..., Mm, where each element M1 of matrix M1 i,j :i=1,...,l 1 ,j=1,...,k means z 1i to sample set The multi-factor directional Hausdorff distance between the jth nearest samples, each element in M2,...,Mm is the same, the specific definition of the multi-factor directional Hausdorff distance is as follows:
[0033] (1) Considering the position characteristics, velocity characteristics and course characteristics of two targets, the multi-factor distanc...
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