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  • 标题:Background Subtraction and Target Classification for Gait Recognition
  • 本地全文:下载
  • 作者:Kantipudi MVV Prasad ; Dr.V.Sailaja ; A. Jagan
  • 期刊名称:International Journal of Computer Technology and Applications
  • 电子版ISSN:2229-6093
  • 出版年度:2011
  • 卷号:2
  • 期号:3
  • 页码:515-520
  • 出版社:Technopark Publications
  • 摘要:This paper deals with background modeling and moving object classification for gait recognition. Current image-based human recognition methods such as fingerprints, face, iris biometric modalities, generally require a cooperative subject views. These methods cannot reliably recognize non cooperating individuals at a distance in the real world under changing environmental conditions. In such conditions, recognition of a person using gait has good advantage. First step in gait recognition is the background subtraction/modeling. This is the crucial step in gait recognition. By using this, identification of moving objects from background scene has to be done. Perfect background subtraction is essential to get a high recognition rate. Next step is the separation of human beings from other moving objects (viz; car, tree etc.). In this paper, we have used a modified background subtraction algorithm and subsequently used feature-based classification of pedestrian from other moving objects. Experimental results demonstrated the effectiveness of the proposed method
  • 关键词:Gaussian Mixture Model; Temporal consistency; Classification metric operator.
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