Abstract
We present Videolytics, a web-based system for advanced analytics over recorded video streams. Video cameras have become widely used for indoor and outdoor surveillance.
Covering even more public space in cities, the cameras serve various purposes ranging from security to traffic monitoring, urban life, and marketing. The goal is to obtain effective and efficient models to process the video data automatically and produce the desired features for data analytics.
Videolytics combines the best of deep learning and hand-designed analytical models to create a solution applicable in real-life situations. The architecture of the Videolytics framework is centered around a database of video features and detected objects, where new higher-level objects result from fusion of (lower-level) objects and features already stored in the database.
The system provides a number of visualization options, an SQL-based analytics module as well as a real-time surveillance mode.