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Object Surveillance and Unusual-behavior Judgment using Network Camera

네트워크 카메라를 이용한 물체 감시와 비정상행위 판단

  • 김진규 (군산대학교 전자정보공학부) ;
  • 주영훈 (군산대학교 제어로봇공학과)
  • Received : 2011.09.23
  • Accepted : 2011.11.27
  • Published : 2012.01.01

Abstract

In this paper, we propose an intelligent method to surveil moving objects and to judge an unusual-behavior by using network cameras. To surveil moving objects, the Scale Invariant Feature Transform (SIFT) algorithm is used to characterize the feature information of objects. To judge unusual-behaviors, the virtual human skeleton is used to extract the feature points of a human in input images. In this procedure, the Principal Component Analysis (PCA) improves the accuracy of the feature vector and the fuzzy classifier provides the judgement principle of unusual-behaviors. Finally, the experiment results show the effectiveness and the feasibility of the proposed method.

Keywords

References

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