Left-object detection through background modeling

Chih Yang Lin, Chi Shiang Chan, Li Wei Kang, Kahlil Muchtar

研究成果: 雜誌貢獻期刊論文同行評審

6 引文 斯高帕斯(Scopus)


Video surveillance systems are becoming extensively deployed in many environments due to the increasing needs of public security and crime prevention. In this paper, we propose a comprehensive solution for managing abandoned objects, which means that the system can deal with objects that are abandoned, removed, or partially occluded. The system contains two adaptive abandoned object detection (AOD) methods that are both based on the proposed texture modeling method associated with a mixture of Gaussians for a real environment. The first method is more efficient than the second one, but the latter is more robust than the former. The proposed methods have been proved to be characterized with prominent efficiency and robustness according to mathematic analyses and experimental results. The designed automatic detection system helps human operators not only to ease tedious monitoring work but also to focus only on suspicious abnormal events.

頁(從 - 到)1373-1388
期刊International Journal of Innovative Computing, Information and Control
出版狀態已發佈 - 2013

ASJC Scopus subject areas

  • 軟體
  • 理論電腦科學
  • 資訊系統
  • 計算機理論與數學


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