Sciweavers

Share
CVPR
2005
IEEE

Detection and Explanation of Anomalous Activities: Representing Activities as Bags of Event n-Grams

13 years 7 months ago
Detection and Explanation of Anomalous Activities: Representing Activities as Bags of Event n-Grams
We present a novel representation and method for detecting and explaining anomalous activities in a video stream. Drawing from natural language processing, we introduce a representation of activities as bags of event n-grams, where we analyze the global structural information of activities using their local event statistics. We demonstrate how maximal cliques in an undirected edge-weighted graph of activities, can be used in an unsupervised manner, to discover regular sub-classes of an activity class. Based on these discovered sub-classes, we formulate a definition of anomalous activities and present a way to detect them. Finally, we characterize each discovered sub-class in terms of its "most representative member," and present an informationtheoretic method to explain the detected anomalies in a human-interpretable form.
Raffay Hamid, Amos Y. Johnson, Samir Batta, Aaron
Added 12 Oct 2009
Updated 29 Oct 2009
Type Conference
Year 2005
Where CVPR
Authors Raffay Hamid, Amos Y. Johnson, Samir Batta, Aaron F. Bobick, Charles L. Isbell, Graham Coleman
Comments (0)
books