Cited By
View all- Mic VZezula P(2022)Concept of Relational Similarity SearchSimilarity Search and Applications10.1007/978-3-031-17849-8_8(89-103)Online publication date: 5-Oct-2022
Videolytics: System for Data Analytics of Video Streams
Authors: 
Tomáš Skopal, Dominika Ďurišková, Petr Pechman, Marek Dobranský, Vladislav KhachaturianAuthors Info & Claims
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.
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Index Terms
- Videolytics: System for Data Analytics of Video Streams
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Published In
October 2021
4966 pages
ISBN:9781450384469
DOI:10.1145/3459637
- General Chairs:
- Gianluca Demartini,
- Guido Zuccon,
- Program Chairs:
- J. Shane Culpepper,
- Zi Huang,
- Hanghang Tong
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Published: 30 October 2021
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CIKM '21: The 30th ACM International Conference on Information and Knowledge Management
November 1 - 5, 2021
Queensland, Virtual Event, Australia
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View all- Mic VZezula P(2022)Concept of Relational Similarity SearchSimilarity Search and Applications10.1007/978-3-031-17849-8_8(89-103)Online publication date: 5-Oct-2022
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