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  • 标题:Active Shape Model-Based Gait Recognition Using Infrared Images
  • 本地全文:下载
  • 作者:Daehee Kim ; Seungwon Lee ; Jooki Paik
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2009
  • 卷号:2
  • 期号:4
  • 出版社:SERSC
  • 摘要:We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affected by the intensity of illumination, it is able to provide constant recognition performance regardless of the amount of illumination. Model-based object tracking algorithms enable robust tracking with partial occlusions or dynamic illumination. However, this algorithm often fails in tracking objects if strong edge exists near the object. Replacement of the input image by an IR image guarantees robust object region extraction because background edges do not affect the IR image. In conclusion, the proposed gait recognition algorithm improves accuracy in object extraction by using IR images and the improvements finally increase the recognition rate of gaits.
  • 关键词:Active shape model; Gait recognition; Object tracking
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