Surveillance video is used in two key modes, watching for known threats in real-time and searching for events of interest after the fact. Typically, real-time alerting is a localized function, e.g. airport security center receives and reacts to a “perimeter breach alert”, while investigations often tend to encompass a large number of geographically distributed cameras like the London bombing, or Washington sniper incidents. Enabling effective search of surveillance video for investigation & preemption, involves indexing the video along multiple dimensions. This paper presents a framework for surveillance search which includes, video parsing, indexing and query mechanisms. It explores video parsing techniques which automatically extract index data from video, indexing which stores data in relational tables, retrieval which uses SQL queries to retrieve events of interest and the software architecture that integrates these technologies.
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