Earticle

초록

영어

Abnormal event detection is a challenging task in video analysis. In this paper, we propose a new abnormal event detection algorithm for surveillance videos. It is well accepted that human eyes are extremely sensitive to abnormal events and they can quickly pay attention to the locations of these abnormal events in visual scenes. Thus, the characteristics of the Human Visual System (HVS) can be used for abnormal event detection. By exploiting the characteristics of the HVS, we propose an abnormal event detection algorithm based on saliency information. Firstly, the saliency information is extracted from video frames based on the feature contrast. The motion information of video frames is calculated by the multi-scale histogram optical flow (MHOF). Based on the features of saliency information and MHOF, the Support Vector Machine (SVM) is used to train and predict the abnormal events in visual scenes. Experimental results show that the proposed abnormal event detection method can obtain much better performance than the existing ones over the public video database.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1. Saliency Information Extraction
  2.2. Multi-Scale Histogram of Optical Flow
  2.3. SVM
 3. The proposed Method
  3.1. Abnormal Event Detection
  3.2. Spatio-Temporal Abnormal Event Detection Model
 4. Experiment
  4.1. Lawn Scene
  4.2. Indoor Scene
  4.3. Plaza Scene
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Zhijun Fang [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China, School of Communication and Information Engineering, Shanghai University, Shanghai, China ]
• Fengchang Fei [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ]
• Yuming Fang [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ] Corresponding author
• Lei Shu [ School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China ]
• Wanggen Wan [ School of Communication and Information Engineering, Shanghai University, Shanghai, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605