Tracking method based on sparse subspace

The invention discloses a tracking method based on a sparse subspace, comprising the steps of firstly learning a plurality of initial frame images by using a random projection matrix and a robust principal component analysis (RPCA) method, and obtaining a low-rank matrix of the images; and extractin...

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Bibliographic Details
Main Authors WU LEI, CHEN PENG, HE RUOBIN, WU DEAN
Format Patent
LanguageChinese
English
Published 06.04.2016
Subjects
CALCULATING
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Summary:The invention discloses a tracking method based on a sparse subspace, comprising the steps of firstly learning a plurality of initial frame images by using a random projection matrix and a robust principal component analysis (RPCA) method, and obtaining a low-rank matrix of the images; and extracting the sparse subspace where a tracked target is located from the low-rank matrix. The sparse subspace obtained according to the method has the characteristics of low complexity and high robustness. Compared with the traditional particle filter method based on the target color, target texture or target template, the algorithm based on the target features mentioned in the text has the characteristics of being less in the number of required particles, high in timeliness and strong in stability.
Bibliography:Application Number: CN20151962960