iSurveillance: Intelligent framework for multiple events detection in surveillance videos
作者：
Highlights：
• It is essential to automate the video surveillance systems due to human limitation.
• Based on the principle of compositionality, this paper proposed the iSurveillance.
• Our work shows good results in detecting multiple events under a unified framework.
• Our work is opposed to prior methods that are tailor-made and designed to work in specific area.
• Future work focus on new domain knowledge, dataset and improve variables complexity.
摘要
•It is essential to automate the video surveillance systems due to human limitation.•Based on the principle of compositionality, this paper proposed the iSurveillance.•Our work shows good results in detecting multiple events under a unified framework.•Our work is opposed to prior methods that are tailor-made and designed to work in specific area.•Future work focus on new domain knowledge, dataset and improve variables complexity.
论文关键词：Video surveillance,Multiple events detection,Compositional modeling
论文评审过程：Available online 15 February 2014.
论文官网地址：https://doi.org/10.1016/j.eswa.2014.02.003
