首页    期刊浏览 2024年11月08日 星期五
登录注册

文章基本信息

  • 标题:A Proficient Extreme Learning Machine Approach For Tracking And Estimating Human Poses
  • 本地全文:下载
  • 作者:Dr.P. Tamije Selvy ; T. Renuka Devi ; R.Siva Keerthini
  • 期刊名称:International Journal of Engineering and Computer Science
  • 印刷版ISSN:2319-7242
  • 出版年度:2015
  • 卷号:4
  • 期号:3
  • 页码:10908-10913
  • 出版社:IJECS
  • 摘要:Tracking and Estimation of human pose in real time is a difficult problem with many interesting applications. Automatedtracking is useful in variety of domains including human computer interaction, gait analysis, the film industry and entertainment. Theexisting system uses different algorithm to estimate and track human poses but the limitation is due to the error rate which is above 10%.In the proposed system effective filtering technique and background subtraction technique is used in order to remove clutters and noises.The objects in each frame are tracked and the corner points are identified. The corner points are used to identify objects that are human.Finally, Extreme Learning Machine classifier is used to identify and estimate the exact human pose from video
  • 关键词:Harris Corner Detection; Gaussian Mixture Model; Extreme Learning Machine; Grey Level Difference Method
国家哲学社会科学文献中心版权所有