Earticle

초록

영어

To avoid fighting and violence occurred in the elevator, this paper proposed an abnormal behavior detection method based on SVM to achieve real-time monitoring. Firstly, the corners of the video sequences were detected and the Lucas-Kanade algorithm was used to calculate the optical flow to obtain velocity vector information. Secondly, this algorithm established a feature vector combining the corner kinetic energy with movement characteristics of targets (including change rate of area, change rate of external rectangle length-width ratio, distance between the targets and the angle difference of target movement direction) as the basis of violent behavior detection. Finally, SVM classifier was constructed to identify the violent behavior. The experiment results showed that the method could detect violent behavior in the elevator effectively and the algorithm was with less complex calculation and higher detection rate thus it could alarm real-time.

목차

Abstract
 1. Introduction
 2. System Fundamentals
  2.1. Foreground Extraction and Identify the Number of People
  2.2. Characteristics Extraction
 3. Support Vector Machine
 4. Experimental Results and Analysis
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Guang Shu [ Department of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China ]
• Gaojing Fu [ Department of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China ]
• Peng Li [ Department of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China ]
• Haiyu Geng [ Department of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605