Detecting abnormal human behaviour using multiple cameras
Signal Processing
Review: The use of pervasive sensing for behaviour profiling - a survey
Pervasive and Mobile Computing
A dynamic hierarchical clustering method for trajectory-based unusual video event detection
IEEE Transactions on Image Processing
Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding
International Journal of Computer Vision
A comprehensive study of visual event computing
Multimedia Tools and Applications
Video based abnormal behavior detection
Proceedings of the 2011 International Conference on Innovative Computing and Cloud Computing
Expert Systems with Applications: An International Journal
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This paper describes a framework for detecting unusual events in surveillance videos. Most surveillance systems consist of multiple video streams, but traditional event detection systems treat individual video streams independently or combine them in the feature extraction level through geometric reconstruction. Our framework combines multiple video streams in the inference level, with a coupled hidden Markov Model (CHMM).We use two-stage training to bootstrap a set of usual events, and train a CHMM over the set. By thresholding the likelihood of a test segment being generated by the model, we build a unusual event detector. We evaluate the performance of our detector through qualitative and quantitative experiments on two sets of real world videos.