AESOP: Adaptive Event detection SOftware using Programming by example

Thangali, A., Prasad, H., Kethamakka, S., Demirdjian, D.

Technologies for Homeland Security(2015)

引用 1|浏览37
暂无评分
摘要
This paper presents AESOP, a software tool for automatic event detection in video. AESOP employs a super- vised learning approach for constructing event models, given training examples from different event classes. A trajectory-based formulation is used for modeling events with an aim towards incorporating invariance to changes in the camera location and orientation parameters. The proposed formulation is designed to accommodate events that involve interactions between two or more entities over an extended period of time. AESOPu0027s event models are formulated as HMMs to improve the event detection algorithmu0027s robustness to noise in input data and to achieve computationally efficient algorithms for event model training and event detection. AESOPu0027s performance is demonstrated on a wide range of different scenarios, including stationary camera surveillance and aerial video footage captured in land and maritime environments.
更多
查看译文
关键词
hidden Markov models,learning (artificial intelligence),software packages,video signal processing,AESOP,HMM,adaptive event detection software,aerial video footage,automatic event detection,computationally efficient algorithms,event detection algorithm,event model construction,event model training,software tool,stationary camera surveillance,supervised learning approach,trajectory-based formulation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要