People identification using shadow dynamics

Yumi Iwashita, Adrian Stoica, Ryo Kurazume

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

13 被引用数 (Scopus)

抄録

People identification has numerous applications, ranging from surveillance/security to robotics. Face and body movement/ gait biometrics are the most important tools for this task. Traditional biometrics use direct observation of the body, yet in some situations a projection may offer more information than the direct signal, for example the shadow of a person observed from overhead, e.g. from an unmanned aerial vehicle, may contain more detail than the top view of the head/body. We introduced the idea of shadow biometrics, exploiting biometrics information in human shadow silhouettes as derived from video imagery; this enables "overhead biometrics", for recognition of human identity and behavior from high altitude airborne platforms using overhead video sequences. In this paper, we provide a demonstration of person identification based on gait recognition from shadow analysis. We describe compensation steps to address shadow variation with conditions of observation (sun position, etc). We define measures of shape variation, such as horizontal stripes on the silhouette, their length change in time determines frequency components (here spherical harmonics) for each gait cycle, which are used for classification by a k-nearest neighbor classifier. A correct classification rate (CCR) of 95 % was obtained. A degradation of CCR from 95 % to 75 % was observed when reduced spatial and temporal resolution from 1cm to 2cm, and from 30fps to 15fps.

本文言語英語
ホスト出版物のタイトル2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
ページ2453-2456
ページ数4
DOI
出版ステータス出版済み - 12 1 2010
イベント2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, 香港
継続期間: 9 26 20109 29 2010

出版物シリーズ

名前Proceedings - International Conference on Image Processing, ICIP
ISSN(印刷版)1522-4880

その他

その他2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country香港
CityHong Kong
Period9/26/109/29/10

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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