吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 51-54.

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Video object extraction method based on active learning SVM

WANG Xue-jun, ZHAO Lin-lin, WANG Shuang   

  1. College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2012-05-20 Published:2013-06-01

Abstract:

A video object extraction method based on active learning SVM was presented.By using the idea of active learning,the traditional SVM was improved,so the extracted video object was more accurately.An adaptive change detection method was used for obtaining the original video object,then the object was chosen for SVM training,and the positive samples were trained for constructing the intensifying classification plane.Experiment results show that the proposed method can overcome the shortage of the traditional SVM,get more exactly object edge,and reduce the computational complexity.

Key words: video object extraction, support vector machine(SVM), adaptive change detection, active learning

CLC Number: 

  • TP391.4

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