Real-time statistical anomaly detection in video

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EhEye is a surveillance recognition software company specializing in public safety and video surveillance by**using analytics and artificial intelligence. Surveillance video cameras are now widely used, however,**surveillance systems are often ineffective due to the need for experienced individuals' continuous attention to a**large number of videos. Automatic and fast detection of anomalous behaviour of individuals, such as fighting,**in a sequence of video frames offers new exciting possibilities for improving this effectiveness, especially for**large, critical infrastructure locations. This will provide a system which can optimize the capabilities of**existing security camera infrastructure and increase the security team's ability to respond to situations in real**time.**There are, however, a number of technical challenges in implementing such an automatic system. This project**will address the two key challenges - namely fast preprocessing of the data and accurate detection of anomalies**in video stream. First, the high dimensional data in each video frame needs to be reduced to the most relevant**low dimensional information needed for effective detection; the computation of this low dimensional**information needs to be performed in real time as video proceeds. Second, an accurate model needs to be**trained based on the extracted low dimensional information to estimate the probability of the fighting scenes**and conclude on it. The model or method for such prediction can be trained off-line but need to run in real time**when applied online.