Abstract
In this demo, we present Wally, a scalable distributed automated video surveillance system. Wally provides users with rich search functionalities for surveillance, such as instant and historical search based on face or clothing feature by specifying multiple conditions. Unlike most existing systems that focus on video analysis but do not well consider system scalability and search functionality, Wally takes into account both of them, and is developed as a commercial level system for realistic surveillance. To achieve this, we 1) employ relational database, in-memory cache, key-value store, and indexing techniques to ensure the system scalability when it meets Big Data, and 2) develop user-friendly interfaces to enable users to search key frames by rich functionalities. It is estimated by our extensive evaluations that Wally can complete a search task within 50 minutes from the videos captured one day by 1000 real-time cameras, while human monitoring needs 1000x24 man-hours.
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